Asymptotical stability in discrete-time neural networks

Weirui Zhao;  Wei Lin;  Rongsong Liu;  Jiong Ruan

doi:10.1109/tcsi.2002.803352

Asymptotical stability in discrete-time neural networks

IEEE Transactions on Circuits and Systems I Fundamental Theory and Applications ◽

10.1109/tcsi.2002.803352 ◽

2002 ◽

Vol 49 (10) ◽

pp. 1516-1520 ◽

Cited By ~ 13

Author(s):

Weirui Zhao ◽

Wei Lin ◽

Rongsong Liu ◽

Jiong Ruan

Keyword(s):

Neural Networks ◽

Discrete Time ◽

Asymptotical Stability

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An asymptotical stability criterion for discrete-time stochastic neural networks with Markovian jumping and time-varying mixed delays

2010 Chinese Control and Decision Conference ◽

10.1109/ccdc.2010.5499090 ◽

2010 ◽

Author(s):

Hongjun Chu ◽

Fang Wang ◽

Lixin Gao

Keyword(s):

Neural Networks ◽

Discrete Time ◽

Stability Criterion ◽

Asymptotical Stability ◽

Stochastic Neural Networks ◽

Mixed Delays ◽

Time Varying ◽

Markovian Jumping

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Chaos and asymptotical stability in discrete-time neural networks

Physica D Nonlinear Phenomena ◽

10.1016/s0167-2789(96)00302-8 ◽

1997 ◽

Vol 104 (3-4) ◽

pp. 286-325 ◽

Cited By ~ 108

Author(s):

Luonan Chen ◽

Kazuyuki Aihara

Keyword(s):

Neural Networks ◽

Discrete Time ◽

Asymptotical Stability

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Chaos and asymptotical stability in discrete-time recurrent neural networks with generalized input-output function

Science in China Series A Mathematics ◽

10.1007/bf02874421 ◽

2001 ◽

Vol 44 (2) ◽

pp. 193-200 ◽

Cited By ~ 5

Author(s):

Jinliang Wang ◽

Luonan Chen ◽

Zhujun Jing

Keyword(s):

Neural Networks ◽

Discrete Time ◽

Recurrent Neural Networks ◽

Asymptotical Stability ◽

Output Function ◽

Input Output

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Globally asymptotical stability of discrete-time analog neural networks

IEEE Transactions on Neural Networks ◽

10.1109/72.508944 ◽

1996 ◽

Vol 7 (4) ◽

pp. 1024-1031 ◽

Cited By ~ 36

Author(s):

Liang Jin ◽

M.M. Gupta

Keyword(s):

Neural Networks ◽

Discrete Time ◽

Asymptotical Stability ◽

Globally Asymptotical Stability ◽

Analog Neural Networks

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Guaranteed cost synchronization of discrete-time chaotic neural networks with missing measurements and randomly occurring sensor nonlinearity

2020 39th Chinese Control Conference (CCC) ◽

10.23919/ccc50068.2020.9188966 ◽

2020 ◽

Author(s):

Hao Zhang ◽

Tong Wang ◽

Qingshuang Zeng ◽

Jianbin Qiu

Keyword(s):

Neural Networks ◽

Discrete Time ◽

Missing Measurements ◽

Chaotic Neural Networks ◽

Guaranteed Cost

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Estimation of the Domain of Attraction of Discrete-Time Impulsive Cohen-Grossberg Neural Networks Model With Impulse Input Saturation

Neural Processing Letters ◽

10.1007/s11063-021-10498-7 ◽

2021 ◽

Author(s):

Zixiang Shen ◽

Chuandong Li ◽

Yi Li

Keyword(s):

Neural Networks ◽

Discrete Time ◽

Input Saturation ◽

Domain Of Attraction

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Discrete-time super-twisting controller using neural networks

Neurocomputing ◽

10.1016/j.neucom.2021.03.060 ◽

2021 ◽

Author(s):

M. Hernandez–Gonzalez ◽

E.A. Hernandez–Vargas

Keyword(s):

Neural Networks ◽

Discrete Time

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On State Estimation for Discrete Time-Delayed Memristive Neural Networks Under the WTOD Protocol: A Resilient Set-Membership Approach

IEEE Transactions on Systems Man and Cybernetics Systems ◽

10.1109/tsmc.2021.3049306 ◽

2021 ◽

pp. 1-11

Author(s):

Hongjian Liu ◽

Zidong Wang ◽

Weiyin Fei ◽

Hongli Dong

Keyword(s):

Neural Networks ◽

State Estimation ◽

Discrete Time ◽

Memristive Neural Networks ◽

Set Membership

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Chaos in the discrete time cellular neural networks

Proceedings of the Third IEEE International Workshop on Cellular Neural Networks and their Applications (CNNA-94) ◽

10.1109/cnna.1994.381663 ◽

2002 ◽

Cited By ~ 2

Author(s):

Chun-Mei Yang ◽

Tao Yang ◽

Kan-Yu Zhang

Keyword(s):

Neural Networks ◽

Discrete Time ◽

Cellular Neural Networks

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An LMI approach to asymptotical stability of multi-delayed neural networks

Physica D Nonlinear Phenomena ◽

10.1016/j.physd.2004.10.009 ◽

2005 ◽

Vol 200 (1-2) ◽

pp. 139-155 ◽

Cited By ~ 75

Author(s):

Xiaofeng Liao ◽

Chuandong Li

Keyword(s):

Neural Networks ◽

Asymptotical Stability ◽

Lmi Approach ◽

Delayed Neural Networks

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