Global Stability Analysis of Neural Networks with Constant Time Delay via Frobenius Norm-Reference-Cited by-同舟云学术

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

Published:2020-10-12 Issue: Volume:2020 Page:1-14
ISSN:1563-5147
Container-title:Mathematical Problems in Engineering
language:en
Short-container-title:Mathematical Problems in Engineering

Author:

Thoiyab N. Mohamed¹,Muruganantham P.¹,Rajchakit Grienggrai²^ORCID,Gunasekaran Nallappan³,Unyong Bundit⁴,Humphries Usa⁵^ORCID,Kaewmesri Pramet⁵,Lim Chee Peng⁶

Affiliation:

1. Department of Mathematics, Jamal Mohamed College, Affiliated to Bharathidasan University, Tiruchirappalli 620020, Tamilnadu, India

2. Department of Mathematics, Faculty of Science, Maejo University, Sansai 50290, Chiang Mai, Thailand

3. Department of Mathematical Sciences, Shibaura Institute of Technology, Saitama 337-8570, Japan

4. Department of Mathematics, Faculty of Science and Technology, Phuket Rajabhat University, Phuket 83000, Thailand

5. Department of Mathematics, Faculty of Science, King Mongkut’s University of Technology Thonburi (KMUTT), 126 Pracha-Uthit Road, Bang Mod, Thung Khru 10140, Thailand

6. Institute for Intelligent Systems Research and Innovation, Deakin University, Waurn Ponds, VIC 3216, Australia

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.

Funder

King Mongkut's University of Technology Thonburi

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

Link

http://downloads.hindawi.com/journals/mpe/2020/4321312.pdf

Reference34 articles.

1. Dynamical analysis of uncertain neural networks with multiple time delays

2. Delay-dependent stability analysis of the QUAD vector field fractional order quaternion-valued memristive uncertain neutral type leaky integrator echo state neural networks

3. Stability analysis of fractional Quaternion-Valued Leaky Integrator Echo State Neural Networks with multiple time-varying delays