The Optimization of Control Parameters: Finite-time and Fixed-time Synchronization of Inertial Memristive Neural Networks with Proportional Delays and Switching Jumps Mismatch

2021 ◽  
Author(s):  
Qi Chang ◽  
Yongqing Yang ◽  
Li Li ◽  
Fei Wang
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Time Synchronization ◽  
Fixed Time ◽  
Control Parameters ◽  
Memristive Neural Networks ◽  
Proportional Delays ◽  
Switching Jumps Mismatch

scholarly journals Finite time Synchronization of Inertial Memristive Neural Networks with Time Varying Delay

2021 ◽  
Vol 16 (4) ◽  
Author(s):  
Yajing Pang ◽  
Shengmei Dong
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Time Synchronization ◽  
Sufficient Conditions ◽  
Lyapunov Stability Theory ◽  
Fixed Time ◽  
Memristive Neural Networks ◽  
Time Varying Delay ◽  
Error System ◽  
Varying Delay

Finite time synchronization control of inertial memristor-based neural networks with varying delay is considered. In view of drive and response concept, the sufficient conditions to ensure finite time synchronization issue of inertial memristive neural networks is given. Based on Lyapunov finite time asymptotic theory, a kind of feedback controllers is designed for inertial memristorbased neural networks to realize the finite time synchronization. Based on Lyapunov stability theory, close loop error system can be proved finite time and fixed time stable. Finally, illustrative example is given to illustrate the effectiveness of theoretical results.

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