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Research Article | Open Access

Stability analysis of neutral-type stochastic delayed neural networks with Markov switching

Xiaohan Nan, Mengdie Li, Xiaoqi Sun( )
School of Mathematics and Statistics, Qingdao University, 308 Ningxia Road, Qingdao 266071, China
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Abstract

This paper investigated the stability of a class of neutral-type stochastic delayed neural networks with Markov switching. Under a general decay rate and weaker conditions on the neutral term, sufficient conditions for stability in the p-th moment, almost sure stability, and actual stability were established by constructing appropriate Lyapunov functions and applying the nonnegative semimartingale convergence theorem. The theoretical analysis was validated via MATLAB simulations using the Euler-Maruyama method.

Keywords

neutral stochastic delayed neural networksp-th moment stabilityMarkov switchinggeneral decayLyapunov function

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Electronic Research Archive
Volume 34 Issue 2,
February 2026
Pages 1095-1123
DOI: 10.3934/era.2026051

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Cite this article:
Nan X, Li M, Sun X. Stability analysis of neutral-type stochastic delayed neural networks with Markov switching. Electronic Research Archive, 2026, 34(2): 1095-1123. https://doi.org/10.3934/era.2026051

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Received: 02 December 2025
Revised: 18 January 2026
Accepted: 26 January 2026
Published: 04 February 2026
©2026 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)