Stability analysis of pseudo almost periodic solutions for octonion-valued recurrent neural networks with proportional delay

Jin Gao, Lihua Dai and Hongying Jiang

Chaos, Solitons & Fractals, 2023, vol. 175, issue P2

Abstract: Considering the effect of the proportional delay, this paper deals with a class of octonion-valued recurrent neural networks with proportional delay. We do not need to decompose the octonion-valued recurrent neural networks into real-valued neural networks because the multiplication of octonion algebras does not satisfy the associativity and commutativity. We obtain several sufficient conditions for the existence and local exponential stability of pseudo almost periodic solutions for octonion-valued recurrent neural networks with proportional delay by using the Banach fixed point theorem, the non-decomposition method, and the Lyapunov function method. Finally, one example will be given to verify the obtained theoretical results.

Keywords: Octonion algebra; Recurrent neural networks; Stability; Pseudo almost periodic solutions; Proportional delay (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:175:y:2023:i:p2:s0960077923009621

DOI: 10.1016/j.chaos.2023.114061

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