Lagrange Exponential Stability of Complex-Valued BAM Neural Networks With Time-Varying Delays

2019 ◽  
pp. 1-14 ◽  
Author(s):  
Ziye Zhang ◽  
Runan Guo ◽  
Xiaoping Liu ◽  
Chong Lin
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
Time Varying ◽  
Bam Neural Networks ◽  
Complex Valued

scholarly journals Impulsive Disturbances on the Dynamical Behavior of Complex-Valued Cohen-Grossberg Neural Networks with Both Time-Varying Delays and Continuously Distributed Delays

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Xiaohui Xu ◽  
Jiye Zhang ◽  
Quan Xu ◽  
Zilong Chen ◽  
Weifan Zheng
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
Equilibrium Point ◽  
Global Exponential Stability ◽  
Dynamical Behavior ◽  
Sufficient Conditions ◽  
Distributed Delays ◽  
Time Varying ◽  
Homeomorphism Mapping ◽  
Complex Valued

This paper studies the global exponential stability for a class of impulsive disturbance complex-valued Cohen-Grossberg neural networks with both time-varying delays and continuously distributed delays. Firstly, the existence and uniqueness of the equilibrium point of the system are analyzed by using the corresponding property of M-matrix and the theorem of homeomorphism mapping. Secondly, the global exponential stability of the equilibrium point of the system is studied by applying the vector Lyapunov function method and the mathematical induction method. The established sufficient conditions show the effects of both delays and impulsive strength on the exponential convergence rate. The obtained results in this paper are with a lower level of conservatism in comparison with some existing ones. Finally, three numerical examples with simulation results are given to illustrate the correctness of the proposed results.

Exponential input-to-state stability for complex-valued memristor-based BAM neural networks with multiple time-varying delays

2018 ◽  
Vol 275 ◽  
pp. 2041-2054 ◽  
Author(s):  
Runan Guo ◽  
Ziye Zhang ◽  
Xiaoping Liu ◽  
Chong Lin ◽  
Haixia Wang ◽  
...  
Keyword(s):  
Neural Networks ◽  
Multiple Time ◽  
Time Varying ◽  
Bam Neural Networks ◽  
Complex Valued
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