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Finite-time stability of almost periodic solutions of Clifford-valued RNNs with time-varying delays and D operator on time scales

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  • Shen, Shiping
  • Meng, Xiaofang

Abstract

The aim of this study is to present the finite-time stability of almost periodic solutions for Clifford-valued recurrent neural networks (RNNs) with time-varying delays and the D operators on time scales using a direct method. In real-world networks, the interactions between network elements are inherently time-delayed, which causes the neural network to oscillate and become unstable. First, some lemmas are obtained by the definitions of almost periodic. Second, by using the theory of calculus for time scales and the Banach fixed point theorem, some sufficient conditions to ensure the finite-time stability of almost periodic solutions for this class of neural networks are obtained. Furthermore, a numerical example is provided to demonstrate the feasibility of the results.

Suggested Citation

  • Shen, Shiping & Meng, Xiaofang, 2023. "Finite-time stability of almost periodic solutions of Clifford-valued RNNs with time-varying delays and D operator on time scales," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    • Handle: RePEc:eee:chsofr:v:169:y:2023:i:c:s0960077923001224
    DOI: 10.1016/j.chaos.2023.113221
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    References listed on IDEAS

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    1. Huang, Chuangxia & Su, Renli & Cao, Jinde & Xiao, Songlin, 2020. "Asymptotically stable high-order neutral cellular neural networks with proportional delays and D operators," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 171(C), pages 127-135.
    2. Grienggrai Rajchakit & Ramalingam Sriraman & Chee Peng Lim & Panu Sam-ang & Porpattama Hammachukiattikul, 2021. "Synchronization in Finite-Time Analysis of Clifford-Valued Neural Networks with Finite-Time Distributed Delays," Mathematics, MDPI, vol. 9(11), pages 1-18, May.
    3. Weide Liu & Jianliang Huang & Qinghe Yao, 2021. "Stability Analysis of Pseudo-Almost Periodic Solution for a Class of Cellular Neural Network with D Operator and Time-Varying Delays," Mathematics, MDPI, vol. 9(16), pages 1-24, August.
    4. Rajchakit, G. & Sriraman, R. & Vignesh, P. & Lim, C.P., 2021. "Impulsive effects on Clifford-valued neural networks with time-varying delays: An asymptotic stability analysis," Applied Mathematics and Computation, Elsevier, vol. 407(C).
    5. Yongkun Li & Chao Wang, 2011. "Almost Periodic Functions on Time Scales and Applications," Discrete Dynamics in Nature and Society, Hindawi, vol. 2011, pages 1-20, July.
    6. Grienggrai Rajchakit & Pharunyou Chanthorn & Pramet Kaewmesri & Ramalingam Sriraman & Chee Peng Lim, 2020. "Global Mittag–Leffler Stability and Stabilization Analysis of Fractional-Order Quaternion-Valued Memristive Neural Networks," Mathematics, MDPI, vol. 8(3), pages 1-29, March.
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    Cited by:

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    2. Zheng, Wei & Zhang, Zhiming & Lam, Hak-Keung & Sun, Fuchun & Wen, Shuhuan, 2023. "LMIs-based exponential stabilization for interval delay systems via congruence transformation: Application in chaotic Lorenz system," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).

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