Global Stability Analysis of Neural Networks with Constant Time Delay via Frobenius Norm. (12th October 2020)

• Record Type: Journal Article
• Authors: Thoiyab, N. Mohamed; Muruganantham, P.; Rajchakit, Grienggrai; Gunasekaran, Nallappan; Unyong, Bundit; Humphries, Usa; Kaewmesri, Pramet; Lim, Chee Peng
• Other Names: Chen Yuming Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2020(2020)
• Publication Date: 2020-10-12
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2020/4321312
• Languages: English
• ISSNs: 1024-123X

Abstract

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.