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

Shiping Shen and Xiaofang Meng

Chaos, Solitons & Fractals, 2023, vol. 169, issue C

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.

Keywords: Almost periodic solutions; Clifford-valued RNNs; Finite-time stability; Time scales (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:169:y:2023:i:c:s0960077923001224

DOI: 10.1016/j.chaos.2023.113221

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