Passivity Analysis of Coupled Stochastic Neural Networks with Multiweights

Author:

Cao Min1ORCID,Yin Xun-Wu2ORCID,Song Wen-He3,Sun Xue-Mei1,Yang Cheng-Dong4ORCID,Ren Shun-Yan5ORCID

Affiliation:

1. Tianjin Key Laboratory of Autonomous Intelligences Technology and System, School of Computer Science and Technology, Tiangong University, Tianjin 300387, China

2. School of Mathematical Sciences, Tiangong University, Tianjin 300387, China

3. Academy of Science and Technology, Tiangong University, Tianjin 300387, China

4. School of Information Science and Technology, Linyi University, Linyi 276005, China

5. School of Mechanical Engineering, Tiangong University, Tianjin 300387, China

Abstract

In this paper, we devote to the investigation of passivity in two types of coupled stochastic neural networks (CSNNs) with multiweights and incompatible input and output dimensions. First, some new definitions of passivity are proposed for stochastic systems that may have incompatible input and output dimensions. By utilizing stochastic analysis techniques and Lyapunov functional method, several sufficient conditions are respectively developed for ensuring that CSNNs without and with multiple delay couplings can realize passivity. Besides, the synchronization criteria for CSNNs with multiweights are established by employing the results of output-strictly passivity. Finally, two simulation examples are given to illustrate the validity of the theoretical results.

Funder

Natural Science Foundation of Tianjin City

Publisher

Hindawi Limited

Subject

Modelling and Simulation

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