Aperiodically Intermittent Control Approach to Finite-Time Synchronization of Delayed Inertial Memristive Neural Networks

Yuxin Jiang, Song Zhu, Mouquan Shen, Shiping Wen, Chaoxu Mu

Research output: Contribution to journalArticlepeer-review

Abstract

This article investigates the finite-time synchronization (FTS) for inertial memristive neural networks (IMNNs) with time-delays by the aperiodically intermittent control approach. Compared with the reduced-order method utilized in the existing literature, this article considers the FTS of delayed IMNNs directly without order reduction. First, the error IMNNs with time-delays is designed through the theories of set-valued mappings and differential inclusions, and its finite-time stability problem is discussed by applying the finite-time stability theorem. Furthermore, by constructing nonperiodic intermittent state-feedback controller and nonperiodic intermittent adaptive control strategy, the sufficient criteria to ensure the FTS of the master-slave delayed IMNNs are derived, and the settling times are explicitly estimated. Finally, a simulation to confirm the availability of results is provided.

Original languageEnglish
Pages (from-to)1014-1023
Number of pages10
JournalIEEE Transactions on Artificial Intelligence
Volume6
Issue number4
DOIs
StatePublished - 2025

Keywords

  • Finite-time stability theorems
  • finite-time synchronization (FTS)
  • inertial memristive neural networks (IMNNs)

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