Robust Stability Analysis of Switched Neural Networks with Application in Psychological Counseling Evaluation System

Yajuan Li and Huanbin Xue ()
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Yajuan Li: School of Education Science, Hanshan Normal University, Chaozhou 521041, China
Huanbin Xue: School of Mathematics and Statistics, Hanshan Normal University, Chaozhou 521041, China

Mathematics, 2024, vol. 12, issue 13, 1-21

Abstract: In this work, the effectiveness and stability of psychological counseling are evaluated using the switched complex-valued neural networks (SCVNN) model, which includes parameter disturbances, impulsive perturbations, variable and continuously distributed delays in the system state, and impulsive delay. How to analyze and judge the stability of the network simply and effectively is the primary prerequisite for its successful application. Therefore, we explore the dynamic behavior of SCVNN with both variable and distributed delays along with impulsive effect. Initially, the proposed conditions for the existence and uniqueness of equilibrium in SCVNN are presented. Subsequently, employing the inequality technique and impulsive average dwell time approach, sufficient conditions for the robust exponential stability of SCVNN under both arbitrary and restricted switching are obtained. Lastly, the psychological counseling evaluation system (PCES) is established, and a simulation example is used to verify the correctness and effectiveness of the presented findings.

Keywords: neural networks; robust stability; switched system; mixed delays (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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