A memristive RBF neural network and its application in unsupervised medical image segmentation
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Chunbiao Li | Zhenyu Lu | Q. Lai | Yongxing Li | Sicong Liu
[1] Rui Huang,et al. Efficient nonlinear aeroelastic analysis of a morphing wing via parameterized fictitious mode method , 2021, Nonlinear Dynamics.
[2] J. N. Tripathi,et al. Uncertainty Quantification of Memristor Crossbar Array for Vector Matrix Multiplication , 2021, 2021 IEEE 25th Workshop on Signal and Power Integrity (SPI).
[3] Tengfei Lei,et al. An amplitude-controllable 3-D hyperchaotic map with homogenous multistability , 2021, Nonlinear Dynamics.
[4] Qiang Lai,et al. A 2D hyperchaotic map with conditional symmetry and attractor growth. , 2021, Chaos.
[5] Julien Clinton Sprott,et al. A simple memristive jerk system , 2021, IET Circuits Devices Syst..
[6] Karthikeyan Rajagopal,et al. A Memristive Hyperjerk Chaotic System: Amplitude Control, FPGA Design, and Prediction with Artificial Neural Network , 2021, Complex..
[7] Jifei Tang,et al. All-digital built-in self-test scheme for charge-pump phase-locked loops , 2020, IET Circuits Devices Syst..
[8] Lin Teng,et al. DMCNN: A Deep Multiscale Convolutional Neural Network Model for Medical Image Segmentation , 2019, Journal of healthcare engineering.
[9] Candace Moore. Image normalization , 2019, Radiopaedia.org.
[10] Alex Pappachen James,et al. Generalized Bell-Shaped Membership Function Generation Circuit for Memristive Neural Networks , 2019, 2019 IEEE International Symposium on Circuits and Systems (ISCAS).
[11] Lei Zhang,et al. Initial value-related dynamical analysis of the memristor-based system with reduced dimensions and its chaotic synchronization via adaptive sliding mode control method , 2019, Chinese Journal of Physics.
[12] QingLian Lin,et al. Facility Layout Planning with SHELL and Fuzzy AHP Method Based on Human Reliability for Operating Theatre , 2019, Journal of healthcare engineering.
[13] Chunbiao Li,et al. Multiple coexisting attractors of the serial–parallel memristor-based chaotic system and its adaptive generalized synchronization , 2018, Nonlinear Dynamics.
[14] Jiafei Yao,et al. Performance Variability, Switching Mechanism, and Physical Model for Oxide Based Memristor and RRAM Device , 2018, 2018 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA).
[15] A. Rubio,et al. On the Variability-aware Design of Memristor-based Logic Circuits , 2018, 2018 IEEE 18th International Conference on Nanotechnology (IEEE-NANO).
[16] Patrick Siarry,et al. Integrating fuzzy entropy clustering with an improved PSO for MRI brain image segmentation , 2018, Appl. Soft Comput..
[17] Anil Singh Parihar,et al. A study on brain tumor segmentation using convolution neural network , 2017, 2017 International Conference on Inventive Computing and Informatics (ICICI).
[18] Fuhong Min,et al. Multistability analysis, circuit implementations and application in image encryption of a novel memristive chaotic circuit , 2017, Nonlinear Dynamics.
[19] Min Fuhong,et al. Dynamic analysis and circuit implementations of a novel memristive chaotic circuit , 2017, 2017 36th Chinese Control Conference (CCC).
[20] Shukai Duan,et al. An improved design of RBF neural network control algorithm based on spintronic memristor crossbar array , 2016, Neural Computing and Applications.
[21] Michael S. Lew,et al. Deep learning for visual understanding: A review , 2016, Neurocomputing.
[22] Chris Yakopcic,et al. Ex-situ training of dense memristor crossbar for neuromorphic applications , 2015, Proceedings of the 2015 IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH´15).
[23] Yasser Iturria-Medina,et al. Statistical analysis of brain tissue images in the wavelet domain: Wavelet-based morphometry , 2013, NeuroImage.
[24] Qiang Chen,et al. Generalized rough fuzzy c-means algorithm for brain MR image segmentation , 2012, Comput. Methods Programs Biomed..
[25] Nicolas Brunel,et al. Sensory neural codes using multiplexed temporal scales , 2010, Trends in Neurosciences.
[26] Juyang Weng,et al. Where-what network 1: “Where” and “what” assist each other through top-down connections , 2008, 2008 7th IEEE International Conference on Development and Learning.
[27] J. Tour,et al. Electronics: The fourth element , 2008, Nature.
[28] Jamshid Ghaboussi,et al. Neural network constitutive model for rate-dependent materials , 2006 .
[29] Ron Kikinis,et al. Improved watershed transform for medical image segmentation using prior information , 2004, IEEE Transactions on Medical Imaging.
[30] R. Kikinis,et al. Cortical gray matter segmentation using an improved watershed-transform , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).
[31] Aly A. Farag,et al. A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data , 2002, IEEE Transactions on Medical Imaging.
[32] Jerry L. Prince,et al. Adaptive fuzzy segmentation of magnetic resonance images , 1999, IEEE Transactions on Medical Imaging.
[33] Jerry L. Prince,et al. Adaptive fuzzy c-means algorithm for image segmentation in the presence of intensity inhomogeneities , 1998, Medical Imaging.
[34] L.O. Chua,et al. Memristive devices and systems , 1976, Proceedings of the IEEE.
[35] L. Chua. Memristor-The missing circuit element , 1971 .
[36] Juan Bautista Roldán,et al. Influence of variability on the performance of HfO2 memristor-based convolutional neural networks , 2021 .
[37] Deep Learning Classifiers with Memristive Networks , 2020, Modeling and Optimization in Science and Technologies.
[38] Alex Pappachen James,et al. Deep Neuro-Fuzzy Architectures , 2019, Modeling and Optimization in Science and Technologies.
[39] Chunbiao Li,et al. A Memristive Chaotic Oscillator With Increasing Amplitude and Frequency , 2018, IEEE Access.
[40] Qi Huang,et al. Image Smoothing , 2015 .
[41] Aiguo Song,et al. Robot Indoor Scenes Recognition Based on Autonomous Developmental Neural Network , 2013 .
[42] R. Dhanasekaran,et al. Fuzzy Clustering and Deformable Model for Tumor Segmentation on MRI Brain Image: A Combined Approach , 2012 .
[43] Shohreh Kasaei,et al. Automatic Brain Tissue Detection in Mri Images Using Seeded Region Growing Segmentation and Neural Network Classification , 2011 .
[44] C E Mackintosh,et al. The combined approach. , 1981, British journal of hospital medicine.
[45] J. Galloway. A Review of the , 1901 .