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Finite-Time Quasi-Synchronization of Delayed BAM Neural Networks Via Laplace Transform Method

  • Zhibin Dai [2] ; Zhengqiu Zhang [1]
    1. [1] Hunan University

      Hunan University

      China

    2. [2] Hunan University of Information Technology
  • Localización: Qualitative theory of dynamical systems, ISSN 1575-5460, Vol. 24, Nº 3, 2025
  • Idioma: inglés
  • Enlaces
  • Resumen

    • In this study, the finite time quasi-synchronization (FTQS) of delayed drive response BAM neural networks (DRBAMNNS) was discussed. Without applying previous study methods of FTQS such as finite-time stability theorems, by using the Laplace transform approach (LTA) and inequality techniques (ITS), two criteria are derived to assure the FTQS for the discussed DRBAMNNS expressed with two differential equations. So far, the LTA has been applied to studying the synchronization of the NNS expressed with a differential equation. However, the studies on the FTQS for NNS expressed with two differential equations have been rare. It is a fact that studying two differential equations is more difficult than studying a differential equation. So, our work is of definite meaning.

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