International Journal of Control, Automation, and Systems 2024; 22(7): 2283-2292
https://doi.org/10.1007/s12555-022-1090-8
© The International Journal of Control, Automation, and Systems
This paper investigates the exponential synchronization of stochastic time-delayed memristor-based neural networks (MBNNs) with using pinning impulsive control. Different from the traditional impulsive control schemes, a hybrid pinning impulsive control scheme is presented, and some sufficient conditions for exponential synchronization of system are established. Moreover, on the basis of the obtained results, the problem of delayed impulsive stabilization of stochastic time-delayed MBNN is studied. At last, an example is provided to demonstrate the validity of the obtained results.
Keywords Delayed impulsive stabilization, exponential synchronization, memristor-based neural networks, pinning impulsive control.
International Journal of Control, Automation, and Systems 2024; 22(7): 2283-2292
Published online July 1, 2024 https://doi.org/10.1007/s12555-022-1090-8
Copyright © The International Journal of Control, Automation, and Systems.
Yao Cui and Pei Cheng*
Anhui University
This paper investigates the exponential synchronization of stochastic time-delayed memristor-based neural networks (MBNNs) with using pinning impulsive control. Different from the traditional impulsive control schemes, a hybrid pinning impulsive control scheme is presented, and some sufficient conditions for exponential synchronization of system are established. Moreover, on the basis of the obtained results, the problem of delayed impulsive stabilization of stochastic time-delayed MBNN is studied. At last, an example is provided to demonstrate the validity of the obtained results.
Keywords: Delayed impulsive stabilization, exponential synchronization, memristor-based neural networks, pinning impulsive control.
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