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Globally asymptotic synchronization for complex-valued BAM neural networks by the differential inequality way

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  • Chen, Dazhao
  • Zhang, Zhengqiu

Abstract

The globally asymptotic synchronization (GAS) topic for the master–slave complex-valued (CV) BAM neural networks (NNS) is approached. Giving up adopting matrix measure way, linear matrix inequality (LMI) means and integral inequality way, by adopting the new study method: the differential inequality way, we get two new criteria guaranteeing that the master CVBAM NNS and the response NNS can reach the GAS. In applying the differential inequality way, the obtaining of two local extremum points and the application of the properties of higher order polynomial are essentially skilful and the results obtained are sufficiently novel. Hence, our study is of important meaning in the study of FTS of NNS.

Suggested Citation

  • Chen, Dazhao & Zhang, Zhengqiu, 2022. "Globally asymptotic synchronization for complex-valued BAM neural networks by the differential inequality way," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    • Handle: RePEc:eee:chsofr:v:164:y:2022:i:c:s0960077922008608
    DOI: 10.1016/j.chaos.2022.112681
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    References listed on IDEAS

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    1. Zhen Yang & Zhengqiu Zhang, 2022. "Global asymptotic synchronisation of fuzzy inertial neural networks with time-varying delays by applying maximum-value approach," International Journal of Systems Science, Taylor & Francis Journals, vol. 53(11), pages 2281-2300, August.
    2. Yang, Xujun & Li, Chuandong & Huang, Tingwen & Song, Qiankun & Huang, Junjian, 2018. "Synchronization of fractional-order memristor-based complex-valued neural networks with uncertain parameters and time delays," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 105-123.
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    Cited by:

    1. Hualin Song & Cheng Hu & Juan Yu, 2022. "Stability and Synchronization of Fractional-Order Complex-Valued Inertial Neural Networks: A Direct Approach," Mathematics, MDPI, vol. 10(24), pages 1-23, December.
    2. 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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