Scholarlink

<p>This paper concentrates on the study of passivity-based synchronization of inertial neural networks including Markov jump parameters. The second-order differential equations are converted into first-order differential equations using the variable transformation method. To make effective use of network bandwidth resources and to optimize the Markov jump inertial neural networks (MJINNs) performance, an adaptive event-driven protocol controller is studied. To achieve synchronization, an appropriate Lyapunov-Krasovskii functional (LKF) is constructed, which includes double integral terms that capture the information of time-varying delay terms. Some sufficient conditions are obtained in terms of linear matrix inequalities (LMIs) using Reciprocal convex combination lemma (RCCL). Then, a numerical simulation and an application of image encryption are carried out to illustrate the effectiveness of the proposed method.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Passivity-based synchronization of Markovian jump inertial neural networks via adaptive event-driven protocol and its application to image encryption

  • 期刊论文

  • 发表日期：

    2026年5月9日

查看全文
  • A. Chandrasekar,
  • Quanxin Zhu,
  • T. Radhika,
  • M. Kamali,
  • A. R. Subhashri

摘要

This paper concentrates on the study of passivity-based synchronization of inertial neural networks including Markov jump parameters. The second-order differential equations are converted into first-order differential equations using the variable transformation method. To make effective use of network bandwidth resources and to optimize the Markov jump inertial neural networks (MJINNs) performance, an adaptive event-driven protocol controller is studied. To achieve synchronization, an appropriate Lyapunov-Krasovskii functional (LKF) is constructed, which includes double integral terms that capture the information of time-varying delay terms. Some sufficient conditions are obtained in terms of linear matrix inequalities (LMIs) using Reciprocal convex combination lemma (RCCL). Then, a numerical simulation and an application of image encryption are carried out to illustrate the effectiveness of the proposed method.