A switching rule for exponential stability of switched recurrent neural networks with interval time-varying delay

• Main Authors: Manlika Rajchakit, Piyapong Niamsup, Grienggrai Rajchakit
• Format: Journal
• Published: 2018
• Subjects: Mathematics
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84878629570&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/52731
• Institution: Chiang Mai University

This paper studies the problem for exponential stability of switched recurrent neural networks with interval time-varying delay. The time delay is a continuous function belonging to a given interval, but not necessarily differentiable. By constructing a set of argumented Lyapunov-Krasovskii functionals combined with the Newton-Leibniz formula, a switching rule for exponential stability of switched recurrent neural networks with interval time-varying delay is designed via linear matrix inequalities, and new sufficient conditions for the exponential stability of switched recurrent neural networks with interval time-varying delay via linear matrix inequalities (LMIs) are derived. A numerical example is given to illustrate the effectiveness of the obtained result. © 2013 Rajchakit et al.; licensee Springer.