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Finite-time synchronization for delayed BAM neural networks by the approach of the same structural functions

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  • Chen, Dazhao
  • Zhang, Zhengqiu

Abstract

In this paper, the finite-time synchronization (FTS) for drive–response BAM neural networks (NNS) are considered. Without using finite-time stability theorems, integral inequality approach and the maximum-valued approach, by using a novel study method: the approach of the same structural functions and designing two classes of novel controllers, two novel sufficient conditions on FTS for the drive–response BAM NNS are proposed. The method and the controllers designed in our paper are very novel.

Suggested Citation

  • Chen, Dazhao & Zhang, Zhengqiu, 2022. "Finite-time synchronization for delayed BAM neural networks by the approach of the same structural functions," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    • Handle: RePEc:eee:chsofr:v:164:y:2022:i:c:s0960077922008347
    DOI: 10.1016/j.chaos.2022.112655
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    1. Chengqiang Wang & Xiangqing Zhao & Can Wang & Zhiwei Lv, 2023. "Synchronization of Takagi–Sugeno Fuzzy Time-Delayed Stochastic Bidirectional Associative Memory Neural Networks Driven by Brownian Motion in Pre-Assigned Settling Time," Mathematics, MDPI, vol. 11(17), pages 1-32, August.

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