N. Kasabov

Mojgan Fard, Maryam Gholami Doborjeh, Krassie Petrova, 2020, 2020 International Conference on Computational Science and Computational Intelligence (CSCI).

Micro-Adaptive Long-Term Traﬃc Forecasting with Evolving Spiking Neural Networks

J. Ser, N. Kasabov, I. Laña, 2018 .

IEEE CIDM 2011 Committee Symposium on Computational Intelligence and Data Mining (IEEE CIDM 2011)

Tamara G. Kolda, Sven F. Crone, Nikola Kasabov, 2011 .

Remote Sensing Dynamic Monitoring of Biological Invasive Species Based on Adaptive PCNN and Improved CV Model 1

N. Kasabov, Yang Jie, P. Gang, 2014 .

Multi-view Geometry Consistency Network for Facial Micro-Expression Recognition From Various Perspectives

N. Kasabov, G. Lu, Yawen Lu, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

A Semi-Online Training Algorithm for the Radial Basis Function Neural Networks: Applications to Bankruptcy Prediction in Banks

Vadlamani Ravi, Nikola Kasabov, P. Ravi Kumar, 2008 .

Machine learning methods for the study of cybersickness: a systematic review

N. Kasabov, Y. Cakmak, Alexander Hui Xiang Yang, 2022, Brain Informatics.

Neural Networks and Logic Programming - a Hybrid Model and its Applicability to Building Expert Systems

Nikola K. Kasabov, S. H. Petkov, N. Kasabov, 1992, European Conference on Artificial Intelligence.

Proceedings of the 23rd International Conference on Artificial Neural Networks and Machine Learning ICANN 2013 - Volume 8131

Günther Palm, Nikola Kasabov, Petia Koprinkova-Hristova, 2013, ICANN 2013.

A Novel Explainable Out-of-Distribution Detection Approach for Spiking Neural Networks

P. G. Bringas, J. Ser, N. Kasabov, 2022, ArXiv.

Personalized Spiking Neural Network Models of Clinical and Environmental Factors to Predict Stroke

V. Feigin, N. Kasabov, R. Krishnamurthi, 2022, Cognitive Computation.

Spatiotemporal EEG Dynamics of Prospective Memory in Ageing and Mild Cognitive Impairment

Josafath Israel Espinosa Ramos, Christina J. Howard, N. Kasabov, 2022, Cognitive Computation.

Advances in Neuro-Information Processing, 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II

Mario Köppen, Nikola Kasabov, George Coghill, 2009, International Conference on Neural Information Processing.

Analysis of the macroeconomic development of European and Asia-Pacific countries with the use of connectionist models

Nikola Kasabov, Jeremiah D. Deng, L Rizzi, 2000 .

Evolving computational intelligence systems

Nikola Kasabov, Plamen Angelov, N. Kasabov, 2005 .

A Fuzzy Neural Network Model for the Estimation ofthe Feeding Rate to an Anaerobic Waste

W. P. Kim, N. Kasabov, R. Kozma, 2008 .

A class of 5D Hamiltonian conservative hyperchaotic systems with symmetry and multistability

N. Kasabov, Qiang Zhang, Shihua Zhou, 2022, Nonlinear Dynamics.

Modelling gene interaction networks from time-series gene expression data using evolving spiking neural networks

N. Kasabov, I. Laña, E. Capecci, 2019, Evolving Systems.

Adaptive cow movement detection using evolving spiking neural network models

N. Kasabov, Tao Gao, 2016, Evolving Systems.

Evolving, dynamic clustering of spatio/spectro-temporal data in 3D spiking neural network models and a case study on EEG data

N. Kasabov, Z. Doborjeh, M. Doborjeh, 2017, Evolving Systems.

Modeling brain dynamics using computational neurogenetic approach

Lubica Benuskova, Nikola Kasabov, N. Kasabov, 2008, Cognitive Neurodynamics.

Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems

Nikola Kasabov, George Coghill, N. Kasabov, 1995 .

Applying Speckle Noise Suppression to Refractive Indices Change Detection in Porous Silicon Microarrays

Zhenhong Jia, Jie Yang, Nikola Kasabov, 2019, Sensors.

eSPANNet: Evolving Spike Pattern Association Neural Network for Spike-based Supervised Incremental Learning and Its Application for Single-trial Brain Computer Interfaces

Nikola Kasabov, Kaushalya Kumarasinghe, Denise Taylor, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

Computational Neurogenetic Modeling: Gene-Dependent Dynamics of Cortex and Idiopathic Epilepsy

Lubica Benuskova, Nikola Kasabov, N. Kasabov, 2014 .

Spiking neural networks for deep learning and knowledge representation: Editorial

Nikola Kasabov, N. Kasabov, 2019, Neural Networks.

Artificial Neural Networks and Machine Learning - ICANN 2013 : 23rd International Conference on Artificial Neural Networks Sofia, Bulgaria, September 10-13, 2013. Proceedings

Günther Palm, Petia Koprinkova-Hristova, Valeri Mladenov, 2013 .

A Novel Medical Image Fusion Approach Based on Nonsubsampled Shearlet Transform

Zhenhong Jia, Nikola Kasabov, Jie Yang, 2019, J. Medical Imaging Health Informatics.

Evolving spiking neural network—a survey

N. Kasabov, S. Schliebs, 2013, Evolving Systems.

Modelling gene interaction networks from time-series gene expression data using evolving spiking neural networks

Nikola K. Kasabov, Josafath Israel Espinosa Ramos, Elisa Capecci, 2019, Evolving Systems.

Discrete Sparse Hashing for Cross-Modal Similarity Search

Lu Wang, Jie Yang, Chao Ma, 2018, ICONIP.

Personalised Modelling for Integrated Static and Dynamic Data. Applications in Neuroinformatics

Nikola Kasabov, N. Kasabov, 2019 .

Improved predictive personalized modelling with the use of Spiking Neural Network system and a case study on stroke occurrences data

Jin Hu, Muhaini Othman, Nikola K. Kasabov, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

Fast Estimation of Distribution Algorithm (EDA) via Constrained Multi-Parent Recombination

Nikola K. Kasabov, Zeke S. H. Chan, N. Kasabov, 2005, SGAI Conf..

Evolving Connectionist Systems with Evolutionary Self-Optimisatio

N. Kasabov, Z. Chan, Q. Song, 2005 .

Evolving Processes and Evolving Connectionist Systems

Nikola Kasabov, N. Kasabov, 2003 .

The Application of Hybrid Evolving Connectionist Systems to Image Classification

Nikola K. Kasabov, Brendon J. Woodford, Steven A. Israel, 2000, J. Adv. Comput. Intell. Intell. Informatics.

Adaptive, Evolving, Hybrid Connectionist Systems for Image Pattern Recognition

Nikola Kasabov, Brendon J. Woodford, Steven I. Israel, 2000 .

Personalised modelling with spiking neural networks integrating temporal and static information

Nikola Kasabov, Zohreh Doborjeh, Maryam Doborjeh, 2019, Neural Networks.

Evolving, dynamic clustering of spatio/spectro-temporal data in 3D spiking neural network models and a case study on EEG data

Maryam Gholami Doborjeh, Nikola K. Kasabov, Zohreh Gholami Doborjeh, 2018, Evol. Syst..

Brain-inspired spiking neural networks for decoding and understanding muscle activity and kinematics from electroencephalography signals during hand movements

N. Kasabov, Denise Taylor, Kaushalya Kumarasinghe, 2021, Scientific Reports.

Attentional Bias Pattern Recognition in Spiking Neural Networks from Spatio-Temporal EEG Data

Maryam Gholami Doborjeh, Nikola K. Kasabov, Zohreh Gholami Doborjeh, 2018, Cognitive Computation.

Brain, gene, and quantum inspired computational intelligence

Nikola Kasabov, N. Kasabov, 2014 .

Understanding Nature Through the Symbiosis of Information Science, Bioinformatics, and Neuroinformatics

Nikola Kasabov, N. Kasabov, 2014 .

Quantum-Inspired Evolutionary Algorithm:

Nikola Kasabov, Stefan Schliebs, Michael Defoin Platel, 2009 .

Computational Modelling and Pattern Recognition in Bioinformatics

Nikola Kasabov, N. Kasabov, 2018, Springer Series on Bio- and Neurosystems.

Data Analysis, Modelling and Knowledge Discovery in Bioinformatics

N. Kasabov, 2003 .

Spiking Neural Network Modelling Approach Reveals How Mindfulness Training Rewires the Brain

Nikola Kasabov, Zohreh Doborjeh, Maryam Doborjeh, 2019, Scientific Reports.

Adaptive long-term traffic state estimation with evolving spiking neural networks

Nikola Kasabov, Javier Del Ser, Elisa Capecci, 2019, Transportation Research Part C: Emerging Technologies.

Spiking Neural Networks for Crop Yield Estimation Based on Spatiotemporal Analysis of Image Time Series

Lorenzo Bruzzone, Nikola K. Kasabov, Reggio N. Hartono, 2016, IEEE Transactions on Geoscience and Remote Sensing.

From von Neumann Machines to Neuromorphic Platforms

Nikola Kasabov, N. Kasabov, 2018, Springer Series on Bio- and Neurosystems.

Gene Regulatory Network Discovery from Time-Series Gene Expression Data - A Computational Intelligence Approach

Nikola K. Kasabov, Vishal Jain, Zeke S. H. Chan, 2004, ICONIP.

Evolving Connectionist Systems for Supervised Learning

Nikola Kasabov, N. Kasabov, 2003 .

Foundations Of Neural Networks, Fuzzy Systems, And Knowledge Engineering [Books in Brief]

Nikola Kasabov, N. Kasabov, 1996, IEEE Transactions on Neural Networks.

Prediction of Preeclampsia and Delivery of Small for Gestational Age Babies Based on a Combination of Clinical Risk Factors in High-Risk Women

Steven H. Wu, L. Poston, N. Kasabov, 2011, Hypertension in pregnancy.

Gene Expression Proé ling of Metastatic and Nonmetastatic Colorectal Cancer Cell Lines

Nikola Kasabov, Matthias E. Futschik, Michael J. Sullivan, 2002 .

Adaptive cow movement detection using evolving spiking neural network models

Tao Gao, Nikola K. Kasabov, N. Kasabov, 2016, Evol. Syst..

Gene Expression Pro ling of Metastatic and Nonmetastatic Colorectal Cancer Cell Lines

Nikola Kasabov, Matthias Futschik, N. Kasabov, 2002 .

Network-Based Method for Inferring Cancer Progression at the Pathway Level from Cross-Sectional Mutation Data

Hao Wu, Nikola K. Kasabov, Lin Gao, 2016, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Training spiking neural networks to associate spatio-temporal input-output spike patterns

Stefan Schliebs, Nikola K. Kasabov, Satoshi Matsuda, 2013, Neurocomputing.

Posterior Distribution Learning (PDL): A novel supervised learning framework using unlabeled samples to improve classification performance

Jie Yang, Nikola K. Kasabov, Enmei Tu, 2015, Neurocomputing.

DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction

Nikola K. Kasabov, Qun Song, N. Kasabov, 2002, IEEE Trans. Fuzzy Syst..

Evolving fuzzy neural networks for supervised/unsupervised online knowledge-based learning

Nikola K. Kasabov, N. Kasabov, 2001, IEEE Trans. Syst. Man Cybern. Part B.

An Integrated Feature Selection and Classification Method to Select Minimum Number of Variables on the Case Study of Gene Expression Data

Liang Goh, Nikola K. Kasabov, N. Kasabov, 2005, J. Bioinform. Comput. Biol..

A Novel Feature Selection Method using Evolving Supervised Clustering and Applications for Gene Expression Data Modeling

Nikola Kasabov, Liang Goh, N. Kasabov, 2002 .

Evolving Intelligence in Humans and Machines: Integrative Evolving Connectionist Systems Approach

N. Kasabov, N. Kasabov, 2008, IEEE Computational Intelligence Magazine.

Integrating evolving brain – gene ontology and connectionist-based system for modeling and knowledge discovery

Nikola K. Kasabov, Vishal Jain, Lubica Benusková, 2008 .

Evolving connectionist systems - the knowledge engineering approach (2. ed.)

Nikola K. Kasabov, N. Kasabov, 2007 .

Computational Intelligence, Bioinformatics and Computational Biology: A Brief Overview of Methods, Problems and Perspectives

Nikola Kasabov, Dimiter S. Dimitrov, Igor A. Sidorov, 2005 .

Air pollution prediction with clustering-based ensemble of evolving spiking neural networks and a case study for London area

Robert Bembenik, Nikola Kasabov, Marzena Kryszkiewicz, 2019, Environ. Model. Softw..

Integrating regression formulas and kernel functions into locally adaptive knowledge-based neural networks: A case study on renal function evaluation

Nikola K. Kasabov, Qun Song, Tianmin Ma, 2006, Artif. Intell. Medicine.

Prediction of tinnitus masking benefit within a case series using a spiking neural network model.

Maryam Gholami Doborjeh, Nikola Kasabov, Zohreh Gholami Doborjeh, 2020, Progress in brain research.

Longitudinal study of a 9p21.3 SNP using a national electronic healthcare database.

H. White, N. Kasabov, J. Mackay, 2010, Personalized medicine.

Neural Information Processing

Rajani K. Mudi, Nikhil R. Pal, Nik Kasabov, 2004, Lecture Notes in Computer Science.

Adaptive modeling and discovery in bioinformatics: The evolving connectionist approach

Nikola K. Kasabov, N. Kasabov, 2008, Int. J. Intell. Syst..

Evolving connectionist systems for knowledge discovery from gene expression data of cancer tissue

Nikola K. Kasabov, Matthias E. Futschik, Anthony Reeve, 2003, Artif. Intell. Medicine.

TTLSC - Transductive Total Least Square Model for Classification and Its Application in Medicine

Nikola K. Kasabov, Qun Song, Tianmin Ma, 2006, ADMA.

TWNFC - Transductive Neural-Fuzzy Classifier with Weighted Data Normalization and Its Application in Medicine

Nikola K. Kasabov, Qun Song, Tianmin Ma, 2005, International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06).

Hybrid system for robust recognition of noisy speech based on evolving fuzzy neural networks and adaptive filtering

Nikola K. Kasabov, Georgi Iliev, N. Kasabov, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Adaptive Filtering with Averaging in Noise Cancellation for Voice and Speech Recognition

Nikola Kasabov, Georgi Iliev, N. Kasabov, 2000 .

CHANNEL EQUALIZATION USING ADAPTIVE FILTERING WITH AVERAGING

Nikola Kasabov, Georgi Iliev, N. Kasabov, 2000 .

Adaptive blind noise suppression in some speech processing applications

Nikola Kasabov, Georgi Iliev, N. Kasabov, 1999, ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378).

Integrative connectionist learning systems inspired by nature: current models, future trends and challenges

Nikola K. Kasabov, N. Kasabov, 2009, Natural Computing.

2008 Special issue Integrating evolving brain-gene ontology and connectionist-based system for modeling and knowledge discovery I

Nikola Kasabov, Lubica Benuskova, Vishal Jain, 2008 .

Brain-, Gene-, and Quantum Inspired Computational Intelligence: Challenges and Opportunities

Nikola K. Kasabov, N. Kasabov, 2007, Challenges for Computational Intelligence.

Neuro-, Genetic-, and Quantum Inspired Evolving Intelligent Systems

N. Kasabov, N. Kasabov, Nikola Kasabov, 2006, 2006 International Symposium on Evolving Fuzzy Systems.

Evolving Connectionist Machines — Framework, Biological Motivation and Implementation Issues

Nikola Kasabov, N. Kasabov, 2003 .

Dynamic Modelling of Brain Functions and Cognitive Processes

Nikola Kasabov, N. Kasabov, 2003 .

Artificial Neural Networks. Evolving Connectionist Systems

Nikola Kasabov, N. Kasabov, 2018, Springer Series on Bio- and Neurosystems.

Evolving Processes in Time-Space. Deep Learning and Deep Knowledge Representation in Time-Space. Brain-Inspired AI

Nikola Kasabov, N. Kasabov, 2018, Springer Series on Bio- and Neurosystems.

Soft Computing Methods for Global, Local and Personalized Modeling and Applications in Bioinformatics

Nikola Kasabov, N. Kasabov, 2009 .

Global, local and personalised modeling and pattern discovery in bioinformatics: An integrated approach

Nikola K. Kasabov, N. Kasabov, 2007, Pattern Recognit. Lett..

Personalized mode transductive spanning SVM classification tree

Shaoning Pang, Youki Kadobayashi, Nikola K. Kasabov, 2011, Inf. Sci..

Modelling Peri-Perceptual Brain Processes in a Deep Learning Spiking Neural Network Architecture

N. Kasabov, A. Sumich, Zohreh Gholami Doborjeh, 2018, Scientific Reports.

Probabilistic Computational Neurogenetic Modeling: From Cognitive Systems to Alzheimer's Disease

Nikola K. Kasabov, Hiroshi Kojima, Reinhard Schliebs, 2011, IEEE Transactions on Autonomous Mental Development.

Detail Preserving Low Illumination Image and Video Enhancement Algorithm Based on Dark Channel Prior

N. Kasabov, Zhen Jia, Jie Yang, 2021, Sensors.

A Fast Sand-Dust Image Enhancement Algorithm by Blue Channel Compensation and Guided Image Filtering

Nikola K. Kasabov, Yaqiao Cheng, Zhenhong Jia, 2020, IEEE Access.

Blue Channel and Fusion for Sandstorm Image Enhancement

Nikola K. Kasabov, Yaqiao Cheng, Zhenhong Jia, 2020, IEEE Access.

A novel multi-focus image fusion method using PCNN in nonsubsampled contourlet transform domain

Zhenhong Jia, Nikola Kasabov, Jie Yang, 2015 .

A dual channel decomposition and remapping fusion model for low illumination images with a wide field of view

N. Kasabov, Zhen Jia, Jie Yang, 2023, Signal Process. Image Commun..

Change Detection in SAR Images Based on the ROF Model Semi-Implicit Denoising Method

Zhenhong Jia, Jie Yang, Nikola K. Kasabov, 2019, Sensors.

Evolving Intelligent Systems: Methodology and Applications

Plamen Angelov, Dimitar Petrov Filev, Nik Kasabov, 2010 .

Low Illumination Video Image Enhancement

Zhi Li, Nikola Kasabov, Zhenhong Jia, 2020, IEEE Photonics Journal.

Spiking neural network methodology for modelling, classification and understanding of EEG spatio-temporal data measuring cognitive processes

Nikola K. Kasabov, Elisa Capecci, N. Kasabov, 2015, Inf. Sci..

Personalized Modeling Based Gene Selection for Microarray Data Analysis

Nikola K. Kasabov, Yingjie Hu, Qun Song, 2008, ICONIP.

Classification consistency analysis for bootstrapping gene selection

Shaoning Pang, Nikola K. Kasabov, Yingjie Hu, 2007, Neural Computing and Applications.

Geomagnetic Storms Can Trigger Stroke: Evidence From 6 Large Population-Based Studies in Europe and Australasia

V. Feigin, C. Anderson, P. Rothwell, 2014, Stroke.

Incremental linear discriminant analysis for classification of data streams

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

Methods of Spiking Neural Networks

Nikola Kasabov, N. Kasabov, 2018, Springer Series on Bio- and Neurosystems.

From von neumann, John Atanasoff and ABC to Neuromorphic computation and the NeuCube spatio-temporal data machine

Nikola K. Kasabov, Neelava Sengupta, Nathan Matthew Scott, 2016, 2016 IEEE 8th International Conference on Intelligent Systems (IS).

Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: Design methodology and selected applications

Maryam Gholami Doborjeh, Muhaini Othman, Jie Yang, 2016, Neural Networks.

Evolving connectionist systems for adaptive learning and knowledge discovery: Trends and directions

Nikola K. Kasabov, N. Kasabov, 2015, Knowl. Based Syst..

Evolving spiking neural networks for personalised modelling, classification and prediction of spatio-temporal patterns with a case study on stroke

Muhaini Othman, Nikola K. Kasabov, Zeng-Guang Hou, 2014, Neurocomputing.

NeuCube: A spiking neural network architecture for mapping, learning and understanding of spatio-temporal brain data

Nikola K. Kasabov, N. Kasabov, 2014, Neural Networks.

Classification and segmentation of fMRI Spatio-Temporal Brain Data with a NeuCube evolving Spiking Neural Network model

Maryam Gholami Doborjeh, Nikola K. Kasabov, Elisa Capecci, 2014, 2014 IEEE Symposium on Evolving and Autonomous Learning Systems (EALS).

Dynamic evolving spiking neural networks for on-line spatio- and spectro-temporal pattern recognition.

Nikola Kasabov, Giacomo Indiveri, Nuttapod Nuntalid, 2013, Neural networks : the official journal of the International Neural Network Society.

NeuCube EvoSpike Architecture for Spatio-temporal Modelling and Pattern Recognition of Brain Signals

Nikola K. Kasabov, N. Kasabov, 2012, ANNPR.

Evolving Spiking Neural Networks and Neurogenetic Systems for Spatio- and Spectro-Temporal Data Modelling and Pattern Recognition

Nikola K. Kasabov, N. Kasabov, 2012, WCCI.

Personalised predictive modelling with brain-inspired spiking neural networks of longitudinal MRI neuroimaging data and the case study of dementia

Nikola Kasabov, Zohreh Doborjeh, Maryam Doborjeh, 2021, Neural Networks.

Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence

Nikola Kasabov, N. Kasabov, 2018, Springer Series on Bio- and Neurosystems.

Integrating Space, Time, and Orientation in Spiking Neural Networks: A Case Study on Multimodal Brain Data Modeling

Nikola Kasabov, Neelava Sengupta, Carolyn B. McNabb, 2018, IEEE Transactions on Neural Networks and Learning Systems.

Mapping, Learning, Visualization, Classification, and Understanding of fMRI Data in the NeuCube Evolving Spatiotemporal Data Machine of Spiking Neural Networks

Maryam Gholami Doborjeh, Nikola K. Kasabov, Zohreh Gholami Doborjeh, 2017, IEEE Transactions on Neural Networks and Learning Systems.

FusionSense: Emotion Classification Using Feature Fusion of Multimodal Data and Deep Learning in a Brain-Inspired Spiking Neural Network

Nikola K. Kasabov, Clarence Tan, Narayan Puthanmadam Subramaniyam, 2020, Sensors.

Application of a Brain-Inspired Spiking Neural Network Architecture to Odor Data Classification

Nikola K. Kasabov, Josafath Israel Espinosa Ramos, Adam Osseiran, 2020, Sensors.

To spike or not to spike: A probabilistic spiking neuron model

Nikola K. Kasabov, N. Kasabov, 2010, Neural Networks.

NeuCubeRehab: A Pilot Study for EEG Classification in Rehabilitation Practice Based on Spiking Neural Networks

Jin Hu, Long Cheng, Nikola K. Kasabov, 2013, ICONIP.

Spiking Neural Networks and Online Learning: An Overview and Perspectives

Albert Bifet, Javier Del Ser, Nikola Kasabov, 2019, Neural Networks.

Span: Spike Pattern Association Neuron for Learning Spatio-Temporal Spike Patterns

Stefan Schliebs, Nikola K. Kasabov, Satoshi Matsuda, 2012, Int. J. Neural Syst..

Spiking Neural Networks for Computational Intelligence: An Overview

Nikola Kasabov, Shirin Dora, N. Kasabov, 2021, Big Data Cogn. Comput..

NeuroSense: Short-term emotion recognition and understanding based on spiking neural network modelling of spatio-temporal EEG patterns

Nikola K. Kasabov, Clarence Tan, Marko Sarlija, 2021, Neurocomputing.

Classification and regression of spatio-temporal signals using NeuCube and its realization on SpiNNaker neuromorphic hardware

Nikola Kasabov, Christoph Richter, Gordon Cheng, 2019, Journal of neural engineering.

Analysis of connectivity in NeuCube spiking neural network models trained on EEG data for the understanding of functional changes in the brain: A case study on opiate dependence treatment

Nikola K. Kasabov, Elisa Capecci, Grace Y. Wang, 2015, Neural Networks.

A spiking neural network model for obstacle avoidance in simulated prosthetic vision

Jie Yang, Nikola K. Kasabov, Chenjie Ge, 2017, Inf. Sci..

A Spiking Neural Network Methodology and System for Learning and Comparative Analysis of EEG Data From Healthy Versus Addiction Treated Versus Addiction Not Treated Subjects

Maryam Gholami Doborjeh, Nikola K. Kasabov, Bruce Russell, 2016, IEEE Transactions on Biomedical Engineering.

Feasibility of NeuCube spiking neural network architecture for EMG pattern recognition

Nikola Kasabov, Hongnian Yu, Luige Vladareanu, 2015, 2015 International Conference on Advanced Mechatronic Systems (ICAMechS).

Spiking Neural Networks: Background, Recent Development and the NeuCube Architecture

Nikola Kasabov, Clarence Tan, Marko Šarlija, 2020, Neural Processing Letters.

Evolving spiking neural networks for audiovisual information processing

Simei Gomes Wysoski, Nikola K. Kasabov, Lubica Benusková, 2010, Neural Networks.

Multiple Time-Series Prediction through Multiple Time-Series Relationships Profiling and Clustered Recurring Trends

Russel Pears, Nikola K. Kasabov, Harya Widiputra, 2011, PAKDD.

DYNAMIC INTERACTION NETWORKS VERSUS LOCAL TREND MODELS FOR MULTIPLE TIME-SERIES PREDICTION

HARYA WIDIPUTRA, RUSSEL PEARS, NIKOLA KASABOV, 2011, Cybern. Syst..

A Practical GrabCut Color Image Segmentation Based on Bayes Classification and Simple Linear Iterative Clustering

Zhenhong Jia, Nikola K. Kasabov, Jie Yang, 2017, IEEE Access.

Are probabilistic spiking neural networks suitable for reservoir computing?

Stefan Schliebs, Nikola K. Kasabov, Ammar Mohemmed, 2011, The 2011 International Joint Conference on Neural Networks.

EEG Pattern Recognition using Brain-Inspired Spiking Neural Networks for Modelling Human Decision Processes

Maryam Gholami Doborjeh, Nikola K. Kasabov, Zohreh Gholami Doborjeh, 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

Building Interpretable Systems in Real Time

Plamen Angelov, Dimitar P. Filev, Nik Kasabov, 2010 .

Single-Image Snow Removal Based on an Attention Mechanism and a Generative Adversarial Network

Nikola K. Kasabov, Jie Yang, Aiwen Jia, 2021, IEEE Access.

Video Snow Removal Based on Self-Adaptation Snow Detection and Patch-Based Gaussian Mixture Model

Nikola K. Kasabov, Zhenhong Jia, Jie Yang, 2020, IEEE Access.

Spatial-temporal adaptation in evolving fuzzy neural networks for on-line adaptive phoneme recognition

Michael J. Watts, Nikola Kasabov, N. Kasabov, 1999 .

Evolving Systems

N. Kasabov, N. K. Kasabov, 2005 .

Dynamic Learning of Multiple Time Series in a Nonstationary Environment

Nikola Kasabov, Russel Pears, Harya Widiputra, 2012 .

HyFIS: adaptive neuro-fuzzy inference systems and their application to nonlinear dynamical systems

Nikola K. Kasabov, Jaesoo Kim, N. Kasabov, 1999, Neural Networks.

Deep Learning and Deep Knowledge Representation of fMRI Data

Nikola Kasabov, N. Kasabov, 2018, Springer Series on Bio- and Neurosystems.

Exploring Associations between Changes in Ambient Temperature and Stroke Occurrence: Comparative Analysis Using Global and Personalised Modelling Approaches

Nikola K. Kasabov, Valery Feigin, Yingjie Hu, 2011, ICONIP.

A versatile quantum-inspired evolutionary algorithm

Michael Defoin-Platel, Stefan Schliebs, Nikola K. Kasabov, 2007, 2007 IEEE Congress on Evolutionary Computation.

Modeling L-LTP based on changes in concentration of pCREB transcription factor

Nikola K. Kasabov, Lubica Benusková, N. Kasabov, 2007, Neurocomputing.

Inductive vs transductive inference, global vs local models: SVM, TSVM, and SVMT for gene expression classification problems

Shaoning Pang, N. Kasabov, N. Kasabov, 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

LDA Merging and Splitting With Applications to Multiagent Cooperative Learning and System Alteration

Shaoning Pang, Youki Kadobayashi, Nikola K. Kasabov, 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

Interpretability of Spatiotemporal Dynamics of the Brain Processes Followed by Mindfulness Intervention in a Brain-Inspired Spiking Neural Network Architecture

Zohreh Doborjeh, Maryam Doborjeh, Mark Crook-Rumsey, 2020, Sensors.

On-line learning, reasoning, rule extraction and aggregation in locally optimized evolving fuzzy neural networks

Nikola K. Kasabov, N. Kasabov, 2001, Neurocomputing.

Evolving Intelligent Systems, eIS

Plamen Angelov, Nik Kasabov, N. Kasabov, 2006 .

Evolving ontologies for intelligent decision support

Nikola Kasabov, Stephen G. MacDonell, Paulo C. M. Gottgtroy, 2006, Fuzzy Logic and the Semantic Web.

Learning a Coordinated Network for Detail-Refinement Multiexposure Image Fusion

N. Kasabov, Shihua Zhou, Jinyuan Liu, 2023, IEEE Transactions on Circuits and Systems for Video Technology.

Neuro-Genetic Information Processing for Optimisation and Adaptation in Intelligent Systems

Nikola Kasabov, N. Kasabov, Michael Watts, 2000 .

Design of MRI structured spiking neural networks and learning algorithms for personalized modelling, analysis, and prediction of EEG signals

M. Jahed-Motlagh, N. Kasabov, A. Tafakhori, 2021, Scientific Reports.

Multispectral Image Enhancement Based on the Dark Channel Prior and Bilateral Fractional Differential Model

Nikola K. Kasabov, Zhenhong Jia, Weijie Chen, 2022, Remote. Sens..

Video Desnowing and Deraining via Saliency and Dual Adaptive Spatiotemporal Filtering

Nikola Kasabov, Jie Yang, Rui Wu, 2021, Sensors.

A Fast Image Segmentation Algorithm Based on Saliency Map and Neutrosophic Set Theory

Nikola K. Kasabov, Jie Yang, Sensen Song, 2020, IEEE Photonics Journal.

Anytime multipurpose emotion recognition from EEG data using a Liquid State Machine based framework

Mariette Awad, Nikola K. Kasabov, Obada Al Zoubi, 2018, Artif. Intell. Medicine.

Unsupervised Change Detection in Wide-Field Video Images Under Low Illumination

N. Kasabov, Zhen Jia, Jie Yang, 2023, IEEE Transactions on Circuits and Systems for Video Technology.

A Multi-Information Fusion Correlation Filters Tracker

Nikola K. Kasabov, Zhenhong Jia, Huicheng Lai, 2020, IEEE Access.

Infrared and visible image fusion based on residual dense network and gradient loss

N. Kasabov, Shihua Zhou, Jinyuan Liu, 2022, Infrared Physics & Technology.

Guest Editorial Evolving Fuzzy Systems–-Preface to the Special Section

Plamen P. Angelov, Dimitar Filev, Nikola K. Kasabov, 2008, IEEE Transactions on Fuzzy Systems.

MUFIS: A neuro-fuzzy inference system using multiple types of fuzzy rules

Nikola K. Kasabov, Qun Song, Yuan-Chun Hwang, 2008, 2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence).

Hybrid neuro-fuzzy inference systems and their application for on-line adaptive learning of nonlinear dynamical systems

Nikola Kasabov, Jaesoo Kim, N. Kasabov, 1999 .

GALFusion: Multi-Exposure Image Fusion via a Global–Local Aggregation Learning Network

N. Kasabov, Shihua Zhou, Qiang Zhang, 2023, IEEE Transactions on Instrumentation and Measurement.

Evolutionary- and Quantum-Inspired Computation. Applications for SNN Optimisation

Nikola Kasabov, N. Kasabov, 2018, Springer Series on Bio- and Neurosystems.

Quantum-inspired particle swarm optimization for feature selection and parameter optimization in evolving spiking neural networks for classification tasks

Siti Mariyam Shamsuddin, Nikola Kasabov, Hn Abdull Hamed, 2011 .

Quantum-inspired particle swarm optimization for feature selection and parameter optimization in evolving spiking neural networks for classification tasks

N. Kasabov, S. Shamsuddin, Nuzly Abdull Hamed, 2011 .

Quantum-Inspired Evolutionary Algorithm: A Multimodel EDA

Michael Defoin-Platel, Stefan Schliebs, Nikola K. Kasabov, 2009, IEEE Transactions on Evolutionary Computation.

Deep learning and deep knowledge representation in Spiking Neural Networks for Brain-Computer Interfaces

Nikola Kasabov, Kaushalya Kumarasinghe, Denise Taylor, 2020, Neural Networks.

A graph-based semi-supervised k nearest-neighbor method for nonlinear manifold distributed data classification pdf

Lin Zhu, Jie Yang, Nikola K. Kasabov, 2016, Inf. Sci..

Ontology Based Personalized Modeling for Type 2 Diabetes Risk Analysis: An Integrated Approach

Francesco Carlo Morabito, Nikola K. Kasabov, Maurizio Fiasché, 2009, ICONIP.

Ontology Based Personalized Modeling for Chronic Disease Risk Analysis: An Integrated Approach

Nikola K. Kasabov, Qun Song, Elaine Rush, 2008, Aust. J. Intell. Inf. Process. Syst..

On the Probabilistic Optimization of Spiking Neural Networks

Michael Defoin-Platel, Stefan Schliebs, Nikola K. Kasabov, 2010, Int. J. Neural Syst..

Simulation of ECB decisions and forecast of short term Euro rate with an adaptive fuzzy expert system

Nikola K. Kasabov, Mario Fedrizzi, Lorenzo Rizzi, 2003, Eur. J. Oper. Res..

Evolving Spiking Neural Networks for online learning over drifting data streams

Javier Del Ser, Nikola K. Kasabov, Jesus L. Lobo, 2018, Neural Networks.

r-SVMT: Discovering the knowledge of association rule over SVM classification trees

Shaoning Pang, Nikola K. Kasabov, N. Kasabov, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

Integrated feature and parameter optimization for an evolving spiking neural network: Exploring heterogeneous probabilistic models

Michael Defoin-Platel, Stefan Schliebs, Nikola K. Kasabov, 2009, Neural Networks.

Evolving Fuzzy Neural Networks for On-line Knowledge Discovery

Nikola Kasabov, N. Kasabov, 2001 .

A fast sand-dust video quality improvement method based on adaptive dynamic guided filtering and interframe detection strategy

Jie Yang, N. Kasabov, Dongdong Ni, 2022, Journal of Real-Time Image Processing.

Modelling the Emergence of Acoustic Segments (Phonemes) in Spoken Languages

Nikola Kasabov, N. Kasabov, 2003 .

Modelling the Emergence of Speech and Language Through Evolving Connectionist Systems

Nikola Kasabov, John R. Taylor, J. Taylor, 2000 .

Future directions for intelligent systems and information sciences : the future of speech and image technologies, brain computers, www, and bioinformatics

Nikola K. Kasabov, N. Kasabov, 2000 .

Sleep Stage Classification using NeuCube on SpiNNaker: a Preliminary Study

Maryam Gholami Doborjeh, Nikola K. Kasabov, Basabdatta Sen Bhattacharya, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Evolving Connectionist Systems: The Knowledge Engineering Approach

Nikola Kasabov, N. Kasabov, 2007 .

Incremental linear discriminant analysis for evolving feature spaces in multitask pattern recognition problems

Nikola K. Kasabov, Seiichi Ozawa, Masayuki Hisada, 2010, Evol. Syst..

Combining neuro-fuzzy and chaos methods for intelligent time series analysis-case study of heart rate variability

Nikola Kasabov, Robert Kozma, J. A. Swope, 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

Encoding and decoding the knowledge of association rules over SVM classification trees

Shaoning Pang, Nikola K. Kasabov, N. Kasabov, 2009, Knowledge and Information Systems.

Integrating Time-Space and Orientation. A Case Study on fMRI + DTI Brain Data

Nikola Kasabov, N. Kasabov, 2018, Springer Series on Bio- and Neurosystems.

Integrative Probabilistic Evolving Spiking Neural Networks Utilising Quantum Inspired Evolutionary Algorithm: A Computational Framework

Nikola K. Kasabov, N. Kasabov, 2008, International Conference on Neural Information Processing.

Knowledge Extraction from Evolving Spiking Neural Networks with Rank Order Population Coding

Snjezana Soltic, Nikola K. Kasabov, N. Kasabov, 2010, Int. J. Neural Syst..

String Pattern Recognition Using Evolving Spiking Neural Networks and Quantum Inspired Particle Swarm Optimization

Nikola K. Kasabov, Siti Mariyam Hj. Shamsuddin, Haza Nuzly Abdul Hamed, 2009, ICONIP.

Integrated Feature Selection and Parameter Optimization for Evolving Spiking Neural Networks Using Quantum Inspired Particle Swarm Optimization

Nikola K. Kasabov, Siti Mariyam Hj. Shamsuddin, Haza Nuzly Abdul Hamed, 2009, 2009 International Conference of Soft Computing and Pattern Recognition.

Integrated Feature and Parameter Optimization for an Evolving Spiking Neural Network

Michael Defoin-Platel, Stefan Schliebs, Nikola K. Kasabov, 2008, ICONIP.

Evolving spiking neural networks for taste recognition

Simei Gomes Wysoski, Snjezana Soltic, Nikola K. Kasabov, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

Computational Neurogenetic Modeling

Nikola Kasabov, Lubica Benuskova, N. Kasabov, 2007 .

On-Line Learning with Structural Adaptation in a Network of Spiking Neurons for Visual Pattern Recognition

Simei Gomes Wysoski, Nikola K. Kasabov, Lubica Benusková, 2006, ICANN.

Special Issue on Advanced Neuro-Fuzzy Techniques and Their Applications: Introduction

Kaoru Hirota, Nikola K. Kasabov, K. Hirota, 1997, Information Sciences.

An Agent Based Framework for Modular Speech Recognition and Language Processing Systems

Nikola K. Kasabov, Andrew R. Gray, Richard Kilgour, 1997, International Conference on Neural Information Processing.

Editorial

Plamen P. Angelov, Dimitar Filev, Nikola K. Kasabov, 2010, Evolutionary Systematics.

Application of an Improved Focal Loss in Vehicle Detection

Nikola K. Kasabov, Xuanlin He, Jie Yang, 2020, ICAISC.

Editorial: Self-Organization and Adaptation in Intelligent Systems

Robert Kozma, Nikola K. Kasabov, N. Kasabov, 1998, Journal of Advanced Computational Intelligence and Intelligent Informatics.

Rule Extraction from Fuzzy Neural Networks FuNN: A Method and a Real-World Application

Robert Kozma, Nikola K. Kasabov, Tico Cohen, 2001, Journal of Advanced Computational Intelligence and Intelligent Informatics.

Spoken language analysis, modeling and recognition - Cstatistical and adaptive connectionist approaches

Nikola K. Kasabov, N. Kasabov, 2003, Information Sciences.

A Retinotopic Spiking Neural Network System for Accurate Recognition of Moving Objects Using NeuCube and Dynamic Vision Sensors

Nikola K. Kasabov, Anne Wendt, Lukas Paulun, 2018, Front. Comput. Neurosci..

Deep Learning of Multisensory Streaming Data for Predictive Modelling with Applications in Finance, Ecology, Transport and Environment

Nikola Kasabov, N. Kasabov, 2018, Springer Series on Bio- and Neurosystems.

Multi-Agent Implementation of Fractal Analysis by Fuzzy Neural Networks

Robert Kozma, Nikola K. Kasabov, J. A. Swope, 1997, International Conference on Neural Information Processing.

Evolving Connectionist Systems and Evolving Brains

Nikola K. Kasabov, N. Kasabov, 1998, International Conference on Neural Information Processing.

A Methodology and a System for Adaptive Speech Recognition in a Noisy Environment Based on Adaptive Noise Cancellation and Evolv- ing Fuzzy Neural Networks

Nikola Kasabov, Georgi Iliev, G. Iliev, 2000 .

Model for exploiting associative matching in AI production systems

Nikola K. Kasabov, Simon H. Lavington, C. Wang, 1995, Knowl. Based Syst..

Audio- and Visual Information Processing in the Brain and Its Modelling with Evolving SNN

Nikola Kasabov, N. Kasabov, 2018, Springer Series on Bio- and Neurosystems.

Deep Learning and Modelling of Audio-, Visual-, and Multimodal Audio-Visual Data in Brain-Inspired SNN

Nikola Kasabov, N. Kasabov, 2018, Springer Series on Bio- and Neurosystems.

An extended Evolving Spiking Neural Network model for spatio-temporal pattern classification

Nikola K. Kasabov, Siti Mariyam Hj. Shamsuddin, Harya Widiputra, 2011, The 2011 International Joint Conference on Neural Networks.

Quantum-inspired feature and parameter optimisation of evolving spiking neural networks with a case study from ecological modeling

Michael Defoin-Platel, Stefan Schliebs, Nikola K. Kasabov, 2009, 2009 International Joint Conference on Neural Networks.

Computational Modeling with Spiking Neural Networks

Nikola Kasabov, Stefan Schliebs, N. Kasabov, 2014 .

Computationa 37. Computational Modeling with Spiking Neural Networks

Nikola Kasabov, Stefan Schliebs, N. Kasabov, 2013 .

Brain-Like System for Audiovisual Person Authentication Based on Time-to-First Spike Coding

Nikola Kasabov, Lubica Benuskova, Simei Gomes Wysoski, 2011 .

Brain-Like Evolving Spiking Neural Networks for Multimodal Information Processing

Simei Gomes Wysoski, Nikola K. Kasabov, Lubica Benusková, 2010, Brain-Inspired Information Technology.

Adaptive Spiking Neural Networks for Audiovisual Pattern Recognition

Simei Gomes Wysoski, Nikola K. Kasabov, Lubica Benusková, 2007, ICONIP.

Text-Independent Speaker Authentication with Spiking Neural Networks

Simei Gomes Wysoski, Nikola K. Kasabov, Lubica Benusková, 2007, ICANN.

Adaptive Learning Procedure for a Network of Spiking Neurons and Visual Pattern Recognition

Simei Gomes Wysoski, Nikola K. Kasabov, Lubica Benusková, 2006, ACIVS.

An Evolving Neural Network Model for Person Verification Combining Speech and Image

David Zhang, Nikola K. Kasabov, Akbar Ghobakhlou, 2004, ICONIP.

AVIS: a connectionist-based framework for integrated auditory and visual information processing

Eric O. Postma, H. Jaap van den Herik, Nikola K. Kasabov, 2000, Inf. Sci..

A Methodology for Speech Data Analysis and a Framework for Adaptive Speech Recognition Using Fuzzy Neural Networks

Michael J. Watts, Robert Kozma, Nikola K. Kasabov, 1997, International Conference on Neural Information Processing.

Brain-like functions in evolving connectionist systems for on-line, knowledge-based learning

Nikola Kasabov, N. Kasabov, 2001 .

Evolving connectionist systems for on-line, knowledge-based learning: Principles and applications

Nikola Kasabov, N. Kasabov, 1999 .

Looking for a new AI paradigm: Evolving connectionist and fuzzy connectionist systems—Theory and applications for adaptive, on-line intelligent systems

Nikola Kasabov, N. Kasabov, 1998 .

Genetic Algorithms for the Design of Fuzzy Neural Networks

Michael J. Watts, Nikola K. Kasabov, N. Kasabov, 1998, ICONIP.

Neuro-Fuzzy and Multivariate Statistical Classification of Fruit Populations Based on Visible-Near Infrared Spectrophotometry Data

Jaesoo Kim, Nikola K. Kasabov, A. Mowat, 1997, International Conference on Neural Information Processing.

Connectionist methods for classification of fruit populations based on visible-near infrared spectrophotometry data

Nikola Kasabov, Jaesoo Kim, Philip Poole, 1998 .

FuNN/2 - A Fuzzy Neural Network Architecture for Adaptive Learning and Knowledge Acquisition

Michael J. Watts, Nikola K. Kasabov, Andrew R. Gray, 1997, Inf. Sci..

Learning fuzzy rules and approximate reasoning in fuzzy neural networks and hybrid systems

Nikola K. Kasabov, N. Kasabov, 1996, Fuzzy Sets Syst..

Drift Detection over Non-stationary Data Streams Using Evolving Spiking Neural Networks

Javier Del Ser, Nikola K. Kasabov, Jesus L. Lobo, 2018, IDC.

基于众包的嵌套流形匹配室内定位方法 (Crowdsourcing-based Indoor Localization via Embedded Manifold Matching)

Zhenhong Jia, Xizhong Qin, Nikola K. Kasabov, 2017, 计算机科学.

The ECOS Framework and the ECO Learning Method for Evolving Connectionist Systems

Nikola K. Kasabov, N. Kasabov, 1998, Journal of Advanced Computational Intelligence and Intelligent Informatics.

Reservoir-Based Evolving Spiking Neural Network for Spatio-temporal Pattern Recognition

Stefan Schliebs, Nikola K. Kasabov, Haza Nuzly Abdul Hamed, 2011, ICONIP.

Towards Spatio-Temporal Pattern Recognition Using Evolving Spiking Neural Networks

Stefan Schliebs, Nikola K. Kasabov, Nuttapod Nuntalid, 2010, ICONIP.

Modeling the emergence of bilingual acoustic clusters: a preliminary case study

Nikola K. Kasabov, Richard Kilgour, Mark R. Laws, 2003, Inf. Sci..

ESOM: an algorithm to evolve self-organizing maps from online data streams

Nikola K. Kasabov, Jeremiah D. Deng, N. Kasabov, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Evolving Self-Organizing Maps for On-line Learning, Data Analysis and Modelling

Nikola Kasabov, Da Deng, N. Kasabov, 2000 .

Modelling the Emergence of Speech Sound Categories in Evolving Connectionist Systems

Nikola Kasabov, Richard Kilgour, John R. Taylor, 2000 .

Evolving connectionist systems: A theory and a case study on adaptive speech recognition

Nikola K. Kasabov, N. Kasabov, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

Independent Component Analysis and Evolving Fuzzy Neural Networks for the Classification of Single Trial EEG Data

A. Cichocki, N. Kasabov, Carl Leichter, 2001 .

A PRACTICAL AND FLEXIBLE ENVIRONMENT FOR ADAPTIVE KNOWLEDGE AND DATA FUSION APPLICATIONS

N. Kasabov, Q. Song, M. Watts, 2000 .

Hybrid Intelligent Decision Support Systems and Applications for Risk Analysis and Discovery of Evolving Economic Clusters in Europe

Nikola Kasabov, Mario Fedrizzi, D. Deng, 2000 .

ECOS — Evolving Connectionist Systems — a New/Old Paradigm for On-line Learning and Knowledge Engineering

Nikola Kasabov, N. Kasabov, 2000 .

On-Line Evolving Fuzzy Clustering

V. Ravi, E.R. Srinivas, N.K. Kasabov, 2007, International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007).

NFI: a neuro-fuzzy inference method for transductive reasoning

Nikola K. Kasabov, Qun Song, N. Kasabov, 2005, IEEE Transactions on Fuzzy Systems.

A Hybrid Genetic Algorithm and Expectation Maximization Method for Global Gene Trajectory Clustering

Nikola K. Kasabov, Zeke S. H. Chan, Lesley Collins, 2005, J. Bioinform. Comput. Biol..

A method for modelling genetic regulatory networks by using evolving connectionist systems and microarray gene expression data

Nikola Kasabov, Dimiter S. Dimitrov, N. Kasabov, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

Evolving Connectionist Systems: Methods and Applications in Bioinformatics, Brain Study and Intelligent Machines

Nikola Kasabov, N. Kasabov, 2002, IEEE Transactions on Neural Networks.

An improved collaborative representation based classification with regularized least square (CRC-RLS) method for robust face recognition

Yu Cheng, Tao Gao, Nikola K. Kasabov, 2016, Neurocomputing.

Stability Analysis for an Online Evolving NeuroFuzzy Recurrent Network

Plamen Angelov, Nik Kasabov, Dimitar P. Filev, 2010 .

A Membership Function Selection Method for Fuzzy Neural Networks

Martin K. Purvis, Nikola K. Kasabov, Quingqing Zhou, 1997, ICONIP.

Transductive Knowledge Based Fuzzy Inference System for Personalized Modeling

Nikola K. Kasabov, Qun Song, Tianmin Ma, 2005, FSKD.

Brain-Gene Ontology: Integrating Bioinformatics and Neuroinformatics Data, Information and Knowledge to Enable Discoveries

Nikola K. Kasabov, Vishal Jain, Frances Joseph, 2006, 2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06).

Emotion Recognition and Understanding Using EEG Data in A Brain-Inspired Spiking Neural Network Architecture

Maryam Gholami Doborjeh, Nikola K. Kasabov, Zohreh Gholami Doborjeh, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

Spiking Neural Network Modelling Approach Reveals How Mindfulness Training Rewires the Brain

Grace Y. Wang, N. Kasabov, A. Sumich, 2019, Scientific Reports.

Spike-time encoding as a data compression technique for pattern recognition of temporal data

Nikola K. Kasabov, Neelava Sengupta, N. Kasabov, 2017, Inf. Sci..

Longitudinal study of alzheimer's disease degeneration through EEG data analysis with a NeuCube spiking neural network model

Francesco Carlo Morabito, Nikola K. Kasabov, Elisa Capecci, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

EEG-based classification of upper-limb ADL using SNN for active robotic rehabilitation

Jin Hu, Nikola K. Kasabov, Zeng-Guang Hou, 2014, 5th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics.

1993 the First New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems, November 24-26, 1993, Dunedin, New Zealand : proceedings

Nikola K. Kasabov, N. Kasabov, 1993 .

Noisy Remote Sensing Image Segmentation with Wavelet Shrinkage and Graph Cuts

Zhenhong Jia, Nikola Kasabov, Jie Yang, 2016, Journal of the Indian Society of Remote Sensing.

Deep Learning of EEG Data in the NeuCube Brain-Inspired Spiking Neural Network Architecture for a Better Understanding of Depression

Maryam Gholami Doborjeh, Nikola K. Kasabov, Grace Y. Wang, 2019, ICONIP.

Evaluating SPAN Incremental Learning for Handwritten Digit Recognition

Nikola K. Kasabov, Guoyu Lu, Ammar Mohemmed, 2012, ICONIP.

Incremental Learning of Chunk Data for Online Pattern Classification Systems

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2008, IEEE Transactions on Neural Networks.

Incremental learning of feature space and classifier for face recognition

Shigeo Abe, Shaoning Pang, Nikola K. Kasabov, 2005, Neural Networks.

Selection and Optimization of Temporal Spike Encoding Methods for Spiking Neural Networks

Nikola Kasabov, Balint Petro, Rita M Kiss, 2020, IEEE Transactions on Neural Networks and Learning Systems.

A Dynamic DNA Color Image Encryption Method Based on SHA-512

Nikola Kasabov, Shihua Zhou, Pinyan He, 2020, Entropy.

sEMG-based torque estimation for robot-assisted lower limb rehabilitation

Jin Hu, Nikola K. Kasabov, Zeng-Guang Hou, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

Deep learning neural networks: Methods, systems, and applications

Zhigang Zeng, Qinglai Wei, Nikola Kasabov, 2020, Neurocomputing.

Deep Learning of Explainable EEG Patterns as Dynamic Spatiotemporal Clusters and Rules in a Brain-Inspired Spiking Neural Network

Maryam Gholami Doborjeh, Nikola K. Kasabov, Zohreh Gholami Doborjeh, 2021, Sensors.

Dynamic 3D Clustering of Spatio-Temporal Brain Data in the NeuCube Spiking Neural Network Architecture on a Case Study of fMRI Data

Maryam Gholami Doborjeh, Nikola K. Kasabov, N. Kasabov, 2015, ICONIP.

Evolving Intelligent Systems: Methods, Learning, & Applications

Nikola Kasabov, Dimitar Filev, Dimitar Filev, 2006, 2006 International Symposium on Evolving Fuzzy Systems.

Estimating risk of events using SOM models: A case study on invasive species establishment

Nikola Kasabov, Susan P. Worner, Joel Pitt, 2006 .

Intelligent Agents and Multi-Agent Systems

Mike Barley, Nik Kasabov, N. Kasabov, 2003, Lecture Notes in Computer Science.

Integrating Spatial and Temporal Information for Violent Activity Detection from Video Using Deep Spiking Neural Networks

Xiang Wang, N. Kasabov, Jie Yang, 2023, Sensors.

Evolving fuzzy neural network for camera operations recognition

Irena Koprinska, Nikola K. Kasabov, N. Kasabov, 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

An Application of Evolving Fuzzy Neural Network for Compressed Video Parsing

Nikola Kasabov, Irena Koprinska, N. Kasabov, 2000 .

An enhanced multiphase Chan–Vese model for the remote sensing image segmentation

Zhenhong Jia, Jie Yang, Nikola K. Kasabov, 2014, Concurr. Comput. Pract. Exp..

Statistical approaches to automatic level set image segmentation with multiple regions

Nikola Kasabov, Jie Yang, Jiangxiong Fang, 2011 .

Multilayer level set method for multiregion image segmentation

Nikola Kasabov, Jie Yang, Jiangxiong Fang, 2011 .

Efficient multiresolution level set image segmentation with multiple regions

Nikola Kasabov, Jie Yang, Jiangxiong Fang, 2011 .

Object Tracking Based on a Time-Varying Spatio-Temporal Regularized Correlation Filter With Aberrance Repression

N. Kasabov, Zhen Jia, Huicheng Lai, 2022, IEEE Photonics Journal.

Constructing Robust Liquid State Machines to Process Highly Variable Data Streams

Stefan Schliebs, Nikola K. Kasabov, Maurizio Fiasché, 2012, ICANN.

Brain-like Computing and Intelligent Information Systems

Nikola Kasabov, Shun-Ichi Amari, S. Amari, 1998 .

Object Motion Deblurring in Single Image Under Static Background

Nikola K. Kasabov, Zhenhong Jia, Jie Yang, 2020, IEEE Access.

SAR Image Change Detection Based on Mathematical Morphology and the K-Means Clustering Algorithm

Zhenhong Jia, Jie Yang, Nikola K. Kasabov, 2019, IEEE Access.

Probabilistic Evolving Spiking Neural Network Optimization Using Dynamic Quantum-inspired Particle Swarm Optimization

Nikola K. Kasabov, Siti Mariyam Hj. Shamsuddin, Haza Nuzly Abdul Hamed, 2010, Aust. J. Intell. Inf. Process. Syst..

Deep Learning and Deep Knowledge Representation in the Human Brain

Nikola Kasabov, N. Kasabov, 2019 .

TWRBF - Transductive RBF Neural Network with Weighted Data Normalization

Nikola K. Kasabov, Qun Song, N. Kasabov, 2004, ICONIP.

WDN-RBF: weighted data normalization for radial basic function type neural networks

N. Kasabov, Qun Song, N. Kasabov, 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

Denoising of Fluorescence Image on the Surface of Quantum Dot/Nanoporous Silicon Biosensors

Y. Liu, N. Kasabov, Zhen Jia, 2022, Sensors.

New Algorithms for Encoding, Learning and Classification of fMRI Data in a Spiking Neural Network Architecture: A Case on Modeling and Understanding of Dynamic Cognitive Processes

Nikola Kasabov, Jie Yang, Lei Zhou, 2017, IEEE Transactions on Cognitive and Developmental Systems.

Correlation Filters with Adaptive Memories and Fusion for Visual Tracking

Jie Yang, Nikola K. Kasabov, Cheng Peng, 2017, ICONIP.

Moving Target Detection Based on Improved Gaussian Mixture Background Subtraction in Video Images

JUNHUI ZUO, ZHENHONG JIA, JIE YANG, 2019, IEEE Access.

ECOS: Evolving Connectionist Systems and the ECO Learning Paradigm

Nikola K. Kasabov, N. Kasabov, 1998, ICONIP.

Incremental and decremental LDA learning with applications

Shaoning Pang, Youki Kadobayashi, Nikola K. Kasabov, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Image and Fractal Information Processing for Large-Scale Chemoinformatics, Genomics Analyses and Pattern Discovery

Shaoning Pang, Nikola K. Kasabov, Vishal Jain, 2006, PRIB.

Salient Object Segmentation Based on Automatic Labeling

Jie Yang, Chen Gong, Yu Qiao, 2013, ICONIP.

Information M 55. Information Methods for Predicting Risk and Outcome of Stroke

Nikola Kasabov, Rita Krishnamurthi, Linda Liang, 2013 .

Two-Class SVM Trees (2-SVMT) for Biomarker Data Analysis

Shaoning Pang, Nikola K. Kasabov, Ilkka Havukkala, 2006, ISNN.

A novel out-of-distribution detection approach for Spiking Neural Networks: Design, fusion, performance evaluation and explainability

N. Kasabov, J. Del Ser, J. Lobo, 2023, Information Fusion.

Salient detection via the fusion of background-based and multiscale frequency-domain features

N. Kasabov, J. Yang, Zhen Jia, 2022, Inf. Sci..

NeuCube Neuromorphic Framework for Spatio-temporal Brain Data and Its Python Implementation

Giacomo Indiveri, Nikola K. Kasabov, Nathan Matthew Scott, 2013, ICONIP.

Global EM Learning of Finite Mixture Models using the Greedy Elimination Method

Nikola K. Kasabov, Zeke S. H. Chan, N. Kasabov, 2005, SGAI Conf..

Computational neurogenetic modeling: integration of spiking neural networks, gene networks, and signal processing techniques

Simei Gomes Wysoski, Nikola K. Kasabov, Lubica Benusková, 2004, IEEE International Workshop on Biomedical Circuits and Systems, 2004..

Modelling and Analysis of Temporal Gene Expression Data Using Spiking Neural Networks

Nikola K. Kasabov, Elisa Capecci, Durgesh Nandini, 2018, ICONIP.

Analysis, Classification and Marker Discovery of Gene Expression Data with Evolving Spiking Neural Networks

Nikola K. Kasabov, Elisa Capecci, Imanol Bilbao, 2018, ICONIP.

Implementation of active training for an upper-limb rehabilitation robot based on impedance control

Nikola Kasabov, Zeng-Guang Hou, Liang Peng, 2015, The 27th Chinese Control and Decision Conference (2015 CCDC).

From Claude Shannon’s Information Entropy to Spike-Time Data Compression Theory

Nikola Kasabov, N. Kasabov, 2018, Springer Series on Bio- and Neurosystems.

A medical image enhancement method using adaptive thresholding in NSCT domain combined unsharp masking

Zhenhong Jia, Lu Liu, Jie Yang, 2015, Int. J. Imaging Syst. Technol..

Evolving spiking neural networks for spatio-and spectro-temporal pattern recognition

Nikola K. Kasabov, N. Kasabov, 2012, 2012 6th IEEE International Conference Intelligent Systems.

Evolving Probabilistic Spiking Neural Networks for Spatio-temporal Pattern Recognition: A Preliminary Study on Moving Object Recognition

Nikola K. Kasabov, Nuttapod Nuntalid, Kshitij Dhoble, 2011, ICONIP.

Evolving and Spiking Connectionist Systems for Brain-Inspired Artificial Intelligence

Nikola Kasabov, N. Kasabov, 2019, Artificial Intelligence in the Age of Neural Networks and Brain Computing.

Evolving Connectionist Systems: From Neuro-Fuzzy-, to Spiking- and Neuro-Genetic

Nikola K. Kasabov, N. Kasabov, 2015, Handbook of Computational Intelligence.

Brain-like Information Processing for Spatio-Temporal Pattern Recognition

Nikola Kasabov, N. Kasabov, 2014 .

The Evolution of the Evolving Neuro-Fuzzy Systems: From Expert Systems to Spiking-, Neurogenetic-, and Quantum Inspired

Nikola K. Kasabov, N. Kasabov, 2013, On Fuzziness.

Unsupervised Change Detection of SAR Images Based on an Improved NSST Algorithm

Zhenhong Jia, Nikola Kasabov, Jie Yang, 2018, Journal of the Indian Society of Remote Sensing.

Rule insertion and rule extraction from evolving fuzzy neural networks: algorithms and applications for building adaptive, intelligent expert systems

N. Kasabov, B. Woodford, N. Kasabov, 1999, FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315).

An evolving spatio-temporal approach for gender and age group classification with Spiking Neural Networks

Russel Pears, Nikola K. Kasabov, Fahad Bashir Alvi, 2018, Evol. Syst..

An evolving spatio-temporal approach for gender and age group classification with Spiking Neural Networks

Fahad Bashir Alvi, N. Kasabov, R. Pears, 2017, Evolving Systems.

NeuCube(ST) for spatio-temporal data predictive modelling with a case study on ecological data

Susan P. Worner, Muhaini Othman, Jie Yang, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

Online spatio-temporal pattern recognition with evolving spiking neural networks utilising address event representation, rank order, and temporal spike learning

Giacomo Indiveri, Nikola K. Kasabov, Nuttapod Nuntalid, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

Framework for Knowledge Driven Optimisation Based Data Encoding for Brain Data Modelling Using Spiking Neural Network Architecture

Nikola Kasabov, Neelava Sengupta, Nathan Scott, 2015 .

Deep semi-supervised learning via dynamic anchor graph embedding in latent space

N. Kasabov, E. Tu, Zihao Wang, 2021, Neural Networks.

Analysis of Gene Expression Time Series Data of Ebola Vaccine response using the NeuCube and Temporal Feature Selection

Nikola K. Kasabov, Elisa Capecci, Lucien Koefoed, 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

Correlation-aided support vector regression for forex time series prediction

Shaoning Pang, Lei Song, Nikola K. Kasabov, 2011, Neural Computing and Applications.

Prediction and detection of virtual reality induced cybersickness: a spiking neural network approach using spatiotemporal EEG brain data and heart rate variability

N. Kasabov, Y. Cakmak, Alexander Hui Xiang Yang, 2023, Brain Informatics.

Medical Image Enhancement Based on Shearlet Transform and Unsharp Masking

Nikola Kasabov, Yang Jie, Ayiguli Wubuli, 2014 .

A Computational Model of Neuroreceptor-Dependent Plasticity (NRDP) Based on Spiking Neural Networks

Nikola Kasabov, Elisa Capecci, Josafath I. Espinosa-Ramos, 2019, IEEE Transactions on Cognitive and Developmental Systems.

Springer Handbook of Bio-/Neuro-Informatics

Nikola Kasabov, N. Kasabov, 2013 .

Fuzzy clustering of gene expression data

Nikola Kasabov, Matthias E. Futschik, N. Kasabov, 2002, 2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291).

String Kernel Based SVM for Internet Security Implementation

Shaoning Pang, Youki Kadobayashi, Nikola K. Kasabov, 2009, ICONIP.

Network-Based Method for Inferring Cancer Progression at the Pathway Level from Cross-Sectional Mutation Data

N. Kasabov, Lin Gao, Hao Wu, 2016, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Identifying overlapping mutated driver pathways by constructing gene networks in cancer

Hao Wu, Feng Li, Xiaofei Yang, 2015, BMC Bioinformatics.

Prediction of Preeclampsia and Delivery of Small for Gestational Age Babies Based on a Combination of Clinical Risk Factors in High-Risk Women

Steven H. Wu, L. Poston, N. Kasabov, 2011, Hypertension in pregnancy.

NeuCube: A spiking neural network architecture for mapping, learning and understanding of spatio-temporal brain data

N. Kasabov, 2014, Neural Networks.

Incremental learning algorithm for spatio-temporal spike pattern classification

Nikola K. Kasabov, Ammar Mohemmed, N. Kasabov, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

A fuzzy neural network model for the estimation of the feeding rate to an anaerobic waste water treatment process

Nikola Kasabov, B Gols, Jaesoo Kim, 1998 .

Biologically Plausible Computational Neurogenetic Models: Modeling the Interaction Between Genes, Neurons and Neural Networks

Nikola Kasabov, Lubica Benuskova, Simei Gomes Wysoski, 2005 .

New avenue for the geriatric depression scale: Rasch transformation enhances reliability of assessment.

V. Feigin, N. Kasabov, P. Sachdev, 2019, Journal of affective disorders.

Learning fuzzy rules through neural networks

Nikola K. Kasabov, N. Kasabov, 1993, Proceedings 1993 The First New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems.

Accurate breast lesion segmentation by exploiting spatio-temporal information with deep recurrent and convolutional network

Hao Zheng, Nikola Kasabov, Jie Yang, 2019, J. Ambient Intell. Humaniz. Comput..

A Spatio-Temporal Fully Convolutional Network for Breast Lesion Segmentation in DCE-MRI

Jie Yang, Nikola K. Kasabov, Hao Zheng, 2018, ICONIP.

Neuro-fuzzy methods for environmental modelling

Nikola Kasabov, Martin Purvis, Qingqing Zhou, 1997 .

Integration of connectionist methods and chaotic time‐series analysis for the prediction of process data

Robert Kozma, Nikola K. Kasabov, J. S. Kim, 1998, Int. J. Intell. Syst..

Learning Fuzzy Production Rules For Approximate Reasoning In Connectionist Production Systems

Nikola Kasabov, N. Kasabov, 1993 .

Evolving Spiking Neural Networks for online learning over drifting data streams

Miren Nekane Bilbao, J. Ser, N. Kasabov, 2018, Neural Networks.

On-line pattern analysis by evolving self-organizing maps

Nikola K. Kasabov, Jeremiah D. Deng, N. Kasabov, 2003, Neurocomputing.

Evolving fuzzy neural networks for supervised/unsupervised online knowledge-based learning

N. Kasabov, 2001, IEEE Trans. Syst. Man Cybern. Part B.

An evolving localised learning model for on-line image colour quantisation

Nikola K. Kasabov, Jeremiah D. Deng, N. Kasabov, 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

Evolving localised learning for on-line colour image quantisation

Nikola Kasabov, Da Deng, N. Kasabov, 2000 .

Methods and systems for intelligent human-computer interaction

Robert Kozma, Nikola K. Kasabov, N. Kasabov, 2000, Inf. Sci..

Dynamic evolving fuzzy neural networks with `m-out-of-n' activation nodes for on-line adaptive systems

Nikola Kasabov, Qun Song, N. Kasabov, 1999 .

Hybrid intelligent adaptive systems: A framework and a case study on speech recognition

Robert Kozma, Nikola K. Kasabov, N. Kasabov, 1998, Int. J. Intell. Syst..

An efficient greedy K-means algorithm for global gene trajectory clustering

Nikola K. Kasabov, Zeke S. H. Chan, Lesley Collins, 2006, Expert Syst. Appl..

Integrative Probabilistic Evolving Spiking Neural Networks Utilising Quantum Inspired Evolutionary Algorithm: A Computational Framework

Nikola K. Kasabov, N. Kasabov, 2008, ICONIP.

Adaptation and interaction in dynamical systems: Modelling and rule discovery through evolving connectionist systems

Nikola K. Kasabov, N. Kasabov, 2006, Appl. Soft Comput..

Knowledge-based neural networks for gene expression data analysis, modelling and profile discovery

Nikola Kasabov, N. Kasabov, 2004 .

Brain, Gene, a 60. Brain, Gene, and Quantum Inspired Computational Intelligence

Nikola Kasabov, N. Kasabov, 2013 .

Fuzzy-Neuro Systems for Local and Personalized Modelling

Nikola Kasabov, Tian Min Ma, Qun Song, 2008 .

A Methodology and a System for Adaptive, Integrated Speech and Image Learning and Recognition

N. Kasabov, A. Ghobakhlou, 2004, Int. J. Comput. Syst. Signals.

Recurrent Evolving Systems, Reinforcement Learning and Evolving Automata

Nikola Kasabov, N. Kasabov, 2003 .

Evolving Connectionist and Fuzzy-Connectionist Systems for On-line Adaptive Decision Making and Control

Nikola Kasabov, N. Kasabov, 1999 .

DNA Matrix Operation Based on the Mechanism of the DNAzyme Binding to Auxiliary Strands to Cleave the Substrate

N. Kasabov, Qiang Zhang, Shihua Zhou, 2021, Biomolecules.

Artificial Neural Networks and Machine Learning – ICANN 2013

Günther Palm, Nikola Kasabov, Petia Koprinkova-Hristova, 2013, Lecture Notes in Computer Science.

Genetic algorithms for structural optimisation, dynamic adaptation and automated design of fuzzy neural networks

Michael J. Watts, Nikola Kasabov, N. Kasabov, 1997, Proceedings of International Conference on Neural Networks (ICNN'97).

Moving object detection in video sequence images based on an improved visual background extraction algorithm

Nikola Kasabov, Jie Yang, Zhenhong Jia, 2020, Multimedia Tools and Applications.

A Biologically Inspired Evolving Spiking Neural Model with Rank-Order Population Coding and a Taste Recognition System Case Study

Nikola Kasabov, Snjezana Soltic, N. Kasabov, 2011 .

Functionally reconfigurable general purpose parallel machines and some image processing and pattern recognition applications

Nikola K. Kasabov, N. Kasabov, 1985, Pattern Recognit. Lett..

Fast neural network ensemble learning via negative-correlation data correction

Nikola K. Kasabov, Zeke S. H. Chan, N. Kasabov, 2005, IEEE Transactions on Neural Networks.

Robust Visual Tracking via Dirac-Weighted Cascading Correlation Filters

Nikola Kasabov, Jie Yang, Fanghui Liu, 2018, IEEE Signal Processing Letters.

Densely Connected Discriminative Correlation Filters for Visual Tracking

Nikola Kasabov, Jie Yang, Fanghui Liu, 2018, IEEE Signal Processing Letters.

Spiking Neural Networks for Text-Independent Speaker Authentication

Nikola Kasabov, Lubica Benuskova, Simei Gomes Wysoski, 2006 .

Studying Transfer of Learning using a Brain-Inspired Spiking Neural Network in the Context of Learning a New Programming Language

Grace Y. Wang, N. Kasabov, K. Petrova, 2021, 2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE).

Short-term ANN load forecasting from limited data using generalization learning strategies

Nikola K. Kasabov, Zeke S. H. Chan, Ahmad B. Rad, 2006, Neurocomputing.

Adaptive speech recognition with evolving connectionist systems

Michael J. Watts, Nikola K. Kasabov, Akbar Ghobakhlou, 2003, Inf. Sci..

Remote Sensing Image Change Detection Based on NSCT-HMT Model and Its Application

Zhenhong Jia, Jie Yang, Nikola K. Kasabov, 2017, Sensors.

From hybrid adjustable neuro-fuzzy systems to adaptive connectionist-based systems for phoneme and word recognition

Nikola K. Kasabov, Richard Kilgour, S. J. Sinclair, 1999, Fuzzy Sets Syst..

Multi-spectral image change detection based on single-band iterative weighting and fuzzy C-means clustering

Nikola Kasabov, Jie Yang, Liyuan Ma, 2020 .

Multi-Spectral Image Change Detection Based on Band Selection and Single-Band Iterative Weighting

Zhenhong Jia, Nikola K. Kasabov, Jie Yang, 2019, IEEE Access.

Reduced feature-set based parallel CHMM speech recognition systems

Waleed H. Abdulla, Nikola K. Kasabov, W. Abdulla, 2003, Inf. Sci..

2005 Special issue: Incremental learning of feature space and classifier for face recognition

Soon Lee Toh, S. Abe, N. Kasabov, 2005 .

A Modified Incremental Principal Component Analysis for On-Line Learning of Feature Space and Classifier

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2004, PRICAI.