Anti-Synchronization in Fixed Time for Discontinuous Reaction-Diffusion Neural Networks With Time-Varying Coefficients and Time Delay

This paper studies the fixed-time anti-synchronization (FTAS) of discontinuous reaction-diffusion neural networks (DRDNNs) with both time-varying coefficients and time delay. First, differential inclusion theory is used to deal with the influence caused by discontinuous activations. In addition, a n...

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Bibliographic Details
Published in:	IEEE transactions on cybernetics Vol. 50; no. 6; pp. 2758 - 2769
Main Authors:	Wang, Zengyun, Cao, Jinde, Cai, Zuowei, Rutkowski, Leszek
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.06.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Adaptive control Algorithms Animals Biological neural networks Coefficients Computer simulation Control algorithms Control systems design Control theory Convergence Delay effects Discontinuous reaction–diffusion neural networks (DRDNNs) Feedback Feedback control fixed-time anti-synchronization (FTAS) integral state-feedback control algorithm Liapunov functions Lyapunov methods Mathematical model Models, Neurological Neural networks Neural Networks, Computer Neurons Neurons - physiology novel state-feedback control algorithm Synchronism Synchronization Time Factors Time lag Time synchronization time-varying coefficient
ISSN:	2168-2267, 2168-2275, 2168-2275
Online Access:	Get full text
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