Design of logic gates using spiking neural P systems with homogeneous neurons and astrocytes-like control
暂无分享,去创建一个
Xun Wang | Pan Zheng | Mou Ling Dennis Wong | Tao Song | Tao Song | Pan Zheng | M. L. D. Wong | Xun Wang
[1] Grzegorz Rozenberg,et al. Handbook of Formal Languages , 1997, Springer Berlin Heidelberg.
[2] Wofgang Maas,et al. Networks of spiking neurons: the third generation of neural network models , 1997 .
[3] Tullio Pozzan,et al. Prostaglandins stimulate calcium-dependent glutamate release in astrocytes , 1998, Nature.
[4] Christopher J. Bishop,et al. Pulsed Neural Networks , 1998 .
[5] Gheorghe Paun,et al. Membrane Computing , 2002, Natural Computing Series.
[6] Rodica Ceterchi,et al. Simulating Boolean Circuits with P Systems , 2003, Workshop on Membrane Computing.
[7] Mihai Ionescu,et al. Boolean Circuits and a DNA Algorithm in Membrane Computing , 2005, Workshop on Membrane Computing.
[8] Rudolf Freund,et al. Extended spiking neural P systems with excitatory and inhibitory astrocytes , 2007 .
[9] Gheorghe Paun. Spiking Neural P Systems with Astrocyte-Like Control , 2007, J. Univers. Comput. Sci..
[10] Mihai Ionescu,et al. Several Applications of Spiking Neural P Systems , 2007 .
[11] G. Perea,et al. Tripartite synapses: astrocytes process and control synaptic information , 2009, Trends in Neurosciences.
[12] Oscar H. Ibarra,et al. Sequential SNP systems based on min/max spike number , 2009, Theor. Comput. Sci..
[13] Oscar H. Ibarra,et al. On spiking neural P systems , 2006, Natural Computing.
[14] Gheorghe Paun,et al. Spiking Neural P Systems: An Overview , 2009 .
[15] Oscar H. Ibarra,et al. Asynchronous spiking neural P systems , 2009, Theor. Comput. Sci..
[16] Miguel A. Gutiérrez-Naranjo,et al. First Steps Towards a CPU Made of Spiking Neural P Systems , 2009, Int. J. Comput. Commun. Control.
[17] Gheorghe Paun,et al. Spiking Neural P Systems with Anti-Spikes , 2009, Int. J. Comput. Commun. Control.
[18] Yoshua Bengio,et al. Why Does Unsupervised Pre-training Help Deep Learning? , 2010, AISTATS.
[19] Kamala Krithivasan,et al. Representation of Spiking Neural P Systems with Anti-spikes through Petri Nets , 2010, BIONETICS.
[20] Gheorghe Paun,et al. The Oxford Handbook of Membrane Computing , 2010 .
[21] Simon Haykin,et al. Neural Networks and Learning Machines , 2010 .
[22] Xiangxiang Zeng,et al. Time-Free Spiking Neural P Systems , 2011, Neural Computation.
[23] Kamala Krithivasan,et al. On String Languages Generated by Spiking Neural P Systems with Anti-Spikes , 2011, Int. J. Found. Comput. Sci..
[24] Linqiang Pan,et al. Spiking Neural P Systems with Astrocytes , 2012, Neural Computation.
[25] Tao Wang,et al. Weighted Fuzzy Spiking Neural P Systems , 2013, IEEE Transactions on Fuzzy Systems.
[26] Linqiang Pan,et al. Asynchronous spiking neural P systems with local synchronization , 2013, Inf. Sci..
[27] Hong Peng,et al. Fuzzy reasoning spiking neural P system for fault diagnosis , 2013, Inf. Sci..
[28] Hong Peng,et al. Adaptive fuzzy spiking neural P systems for fuzzy inference and learning , 2013, Int. J. Comput. Math..
[29] Linqiang Pan,et al. Normal Forms for Some Classes of Sequential Spiking Neural P Systems , 2013, IEEE Transactions on NanoBioscience.
[30] Linqiang Pan,et al. A Novel Bio-Sensor Based on DNA Strand Displacement , 2014, PloS one.
[31] Xiangxiang Zeng,et al. On Some Classes of Sequential Spiking Neural P Systems , 2014, Neural Computation.
[32] Ferrante Neri,et al. An Optimization Spiking Neural P System for Approximately Solving Combinatorial Optimization Problems , 2014, Int. J. Neural Syst..
[33] Xiang Feng,et al. Double-fold localized multiple matrixized learning machine , 2015, Inf. Sci..
[34] Xiangrong Liu,et al. Implementation of Arithmetic Operations With Time-Free Spiking Neural P Systems , 2015, IEEE Transactions on NanoBioscience.
[35] Jürgen Schmidhuber,et al. Deep learning in neural networks: An overview , 2014, Neural Networks.
[36] Linqiang Pan,et al. Spiking Neural P Systems With Rules on Synapses Working in Maximum Spikes Consumption Strategy , 2015, IEEE Transactions on NanoBioscience.
[37] L. Pan,et al. Spiking Neural P Systems With Rules on Synapses Working in Maximum Spiking Strategy , 2015 .
[38] Henry N. Adorna,et al. Spiking neural P systems with structural plasticity , 2015, Neural Computing and Applications.
[39] Zhengyou He,et al. Fault Diagnosis of Electric Power Systems Based on Fuzzy Reasoning Spiking Neural P Systems , 2015, IEEE Transactions on Power Systems.
[40] Xin Li,et al. A Spiking Neural System Based on DNA Strand Displacement , 2015 .
[41] Linqiang Pan,et al. Spiking Neural P Systems With Rules on Synapses Working in Maximum Spiking Strategy , 2014, IEEE Transactions on NanoBioscience.
[42] Shitong Wang,et al. Evolutionary sampling: A novel way of machine learning within a probabilistic framework , 2015, Inf. Sci..
[43] Juan A. Botía Blaya,et al. Generation of human computational models with machine learning , 2015, Inf. Sci..
[44] Nikola K. Kasabov,et al. Spiking neural network methodology for modelling, classification and understanding of EEG spatio-temporal data measuring cognitive processes , 2015, Inf. Sci..
[45] Mario J. Pérez-Jiménez,et al. Fuzzy Membrane Computing: Theory and Applications , 2015, Int. J. Comput. Commun. Control.
[46] Yun Zhu,et al. Efficient parallel boolean matrix based algorithms for computing composite rough set approximations , 2016, Inf. Sci..
[47] Qinghua Hu,et al. Multi-document summarization via group sparse learning , 2016, Inf. Sci..
[48] Linqiang Pan,et al. Cell-like spiking neural P systems , 2016, Theor. Comput. Sci..
[49] Xun Wang,et al. A computational approach for nuclear export signals identification using spiking neural P systems , 2018, Neural Computing and Applications.
[50] Inés Couso,et al. Machine learning models, epistemic set-valued data and generalized loss functions: An encompassing approach , 2016, Inf. Sci..
[51] Linqiang Pan,et al. Spiking neural P systems with request rules , 2016, Neurocomputing.
[52] Xin Li,et al. Construction of DNA nanotubes with controllable diameters and patterns using hierarchical DNA sub-tiles. , 2016, Nanoscale.
[53] Pan Zheng,et al. On the Computational Power of Spiking Neural P Systems with Self-Organization , 2016, Scientific Reports.
[54] Hui Gao,et al. Neuro-adaptive fault-tolerant control of high speed trains under traction-braking failures using self-structuring neural networks , 2016, Inf. Sci..
[55] Marian Gheorghe,et al. Kernel P Systems and Stochastic P Systems for Modelling and Formal Verification of Genetic Logic Gates , 2017 .