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<p>This paper focuses on investigating Markovian jump-switched cellular neural networks (MJSCNNs) using an improved memory event-triggered control approach. The proposed memory event-triggered scheme (METS) has distinct advantages. The information of certain recent released signals are first utilized, which helps to improve the triggering instants and we design a time-varying, state-dependent threshold parameter that adjusts the packet transmission rate based on state information. We formulate a suitable Lyapunov function to demonstrate exponential stability by utilizing integral inequality approaches. The establishment of linear matrix inequalities facilitates the construction of an improved METS co-designed for MJSCNNs. Furthermore, using the average dwell-time method, a collection of adequate criteria. We provided numerical examples to validate and demonstrate the efficacy of our theoretical findings.</p>

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Exponential stability analysis of Markovian jumping switched cellular neural networks via memory-event-triggered control

  • 期刊论文

  • 发表日期：

    2025年4月9日

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  • R. Suresh,
  • M. Meiyanathan,
  • R. Vadivel,
  • S. Saravanan

摘要

This paper focuses on investigating Markovian jump-switched cellular neural networks (MJSCNNs) using an improved memory event-triggered control approach. The proposed memory event-triggered scheme (METS) has distinct advantages. The information of certain recent released signals are first utilized, which helps to improve the triggering instants and we design a time-varying, state-dependent threshold parameter that adjusts the packet transmission rate based on state information. We formulate a suitable Lyapunov function to demonstrate exponential stability by utilizing integral inequality approaches. The establishment of linear matrix inequalities facilitates the construction of an improved METS co-designed for MJSCNNs. Furthermore, using the average dwell-time method, a collection of adequate criteria. We provided numerical examples to validate and demonstrate the efficacy of our theoretical findings.