Global Stability Analysis of Neural Networks with Constant Time Delay via Frobenius Norm

N. Mohamed Thoiyab, P. Muruganantham, Grienggrai Rajchakit, Nallappan Gunasekaran, Bundit Unyong, Usa Humphries, Pramet Kaewmesri and Chee Peng Lim

Mathematical Problems in Engineering, 2020, vol. 2020, 1-14

Abstract:

This paper deals with the global asymptotic robust stability (GARS) of neural networks (NNs) with constant time delay via Frobenius norm. The Frobenius norm result has been utilized to find a new sufficient condition for the existence, uniqueness, and GARS of equilibrium point of the NNs. Some suitable Lyapunov functional and the slope bounded functions have been employed to find the new sufficient condition for GARS of NNs. Finally, we give some comparative study of numerical examples for explaining the advantageous of the proposed result along with the existing GARS results in terms of network parameters.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:4321312

DOI: 10.1155/2020/4321312

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