On the Weighted Pseudo Almost-Periodic Solutions of Static DMAM Neural Network

被引：0
作者：
Mohammed Salah M’hamdi
机构：
[1] University of Bejaia,Research Unit LaMOS, Department of Mechanical Engineering, Faculty of Technology
来源：
Neural Processing Letters | 2022年 / 54卷
关键词：
Static multidirectional associative memory neural network; Time-varying delay; Weighted pseudo almost-periodic function; Global exponential stability; 34C27; 37B25; 92C20;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This work is devoted to study a new class of static neural network. We propose a static multidirectional associative memory neural network with time-varying coefficients and delays. We assess the existence and global exponential stability of weighted pseudo almost-periodic solutions for the systems through exponential dichotomy theory, contraction mapping fixed point theorem, differential inequality techniques and weighted pseudo almost-periodic functions. The theoretical results obtained are supported with numerical simulations. To our knowledge, no paper in the literature has investigated the existence and the delay-independent stability of weighted pseudo almost-periodic solution for static delayed MAM neural network. The results obtained are new and complements that found in the literature.
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页码：4443 / 4464
页数：21
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