Finite‐time synchronization and adaptive synchronization of memristive recurrent neural networks with delays
Copyright policy )Finite‐time synchronization and adaptive synchronization of memristive recurrent neural networks with delays
SummaryThis paper solves the finite‐time synchronization and adaptive synchronization problems of drive‐response memristive recurrent neural networks with delays under two control methods. First, the state‐feedback control rule containing delays and the adaptive control rule are designed for realizing synchronization of drive‐response memristive recurrent neural networks in finite time. Then, on the basis of the Lyapunov stability theory, many algebraic sufficient conditions are obtained to guarantee finite‐time synchronization and adaptive synchronization of drive‐response memristive recurrent neural networks via two control methods, which are easily verified. In addition, the estimation of the upper bounds of the settling time of finite‐time synchronization is obtained. Lastly, to illustrate the effectiveness of the obtained theoretical results, two examples are given.
- Donghua University China (People's Republic of)
- Yancheng Institute of Technology China (People's Republic of)
finite-time synchronization, Discrete-time control/observation systems, Adaptive control/observation systems, Learning and adaptive systems in artificial intelligence, memristive recurrent neural networks, state-feedback control, Lyapunov and other classical stabilities (Lagrange, Poisson, \(L^p, l^p\), etc.) in control theory, Feedback control, Neural networks for/in biological studies, artificial life and related topics, adaptive control
finite-time synchronization, Discrete-time control/observation systems, Adaptive control/observation systems, Learning and adaptive systems in artificial intelligence, memristive recurrent neural networks, state-feedback control, Lyapunov and other classical stabilities (Lagrange, Poisson, \(L^p, l^p\), etc.) in control theory, Feedback control, Neural networks for/in biological studies, artificial life and related topics, adaptive control
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