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Quasi-invariant and attracting sets of competitive neural networks with time-varying and infinite distributed delays

Author

Listed:
  • Yang, Jin
  • Jian, Jigui

Abstract

This paper focuses on the quasi-invariant set (QIS), global attracting set (GAS) and global exponential attracting set (GEAS) of competitive neural networks (CNNs) with time-varying and infinite distributed delays. For these purposes, based on the characteristics of nonnegative matrix and M-matrix, a new bidirectional delay integral inequality and a novel integro-differential inequality are first established. From the founded integral inequality, the existence conditions of the QIS and the GAS of the discussed system are obtained. Besides, the existence conditions of the GEAS are also given by the proposed integro-differential inequality, which gets rid of the construction of complex Lyapunov functions and functionals. The frameworks of the QIS, GAS and GEAS are also given. A numerical example is analyzed to confirm the validity of the obtained results in the end.

Suggested Citation

  • Yang, Jin & Jian, Jigui, 2023. "Quasi-invariant and attracting sets of competitive neural networks with time-varying and infinite distributed delays," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
    • Handle: RePEc:eee:chsofr:v:177:y:2023:i:c:s0960077923011621
    DOI: 10.1016/j.chaos.2023.114260
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    References listed on IDEAS

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    1. Shi, Zhicheng & Yang, Yongqing & Chang, Qi & Xu, Xianyun, 2020. "The optimal state estimation for competitive neural network with time-varying delay using Local Search Algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    2. Peng, Qiu & Jian, Jigui, 2021. "Estimating the ultimate bounds and synchronization of fractional-order plasma chaotic systems," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    3. Wang, Shasha & Jian, Jigui, 2023. "Predefined-time synchronization of fractional-order memristive competitive neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
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