Passivity Analysis of Markov Jump Inertial Neural Networks Subject to Reaction-Diffusion

2021 ◽  
Author(s):  
Lin Sun ◽  
Xuelian Wang ◽  
Yuqing Qin ◽  
Lei Su ◽  
Hao Shen ◽  
...  
Keyword(s):  
Neural Networks ◽  
Reaction Diffusion ◽  
Markov Jump ◽  
Passivity Analysis ◽  
Inertial Neural Networks

Extended dissipative-based state estimation for Markov jump coupled neural networks with reaction-diffusion terms

2021 ◽  
pp. 014233122110282
Author(s):  
Dongxiao Hu ◽  
Xiaona Song ◽  
Xingru Li
Keyword(s):  
Neural Networks ◽  
State Estimation ◽  
Dynamic Error ◽  
Signal Transmission ◽  
Reaction Diffusion ◽  
Linear Matrix ◽  
Markov Jump ◽  
Memory Controller ◽  
Coupled Neural Networks ◽  
Error System

This work mainly concentrates on the state estimation for Markov jump coupled neural networks (MJCNNs) with reaction-diffusion terms, in which the memory controller is employed. First, the considered MJCNNs model is introduced, and the dynamic error system can be obtained based on the proposed state estimator. Then, a memory controller that involves constant signal transmission delay is designed. Moreover, by Lyapunov functional method, inequality technique and Kronecker product law, a novel stable and extended dissipative analysis criteria can be established to ensure that the stability of the error system the error system. Meanwhile, the controller gains can be obtained by solving linear matrix inequalities. Finally, a numerical example is given to illustrate the effectiveness of the developed method.

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