A new approach based on discrete-time high-order neural networks with delays and impulses. Issue 11 (July 2018)

• Record Type: Journal Article
• Authors: Wang, Jinling; Jiang, Haijun; Ma, Tianlong; Hu, Cheng
• Is Part Of: Journal of the Franklin Institute. Volume 355:Issue 11(2018)
• Page Start: 4708
• Page End: 4726
• Publication Date: 2018-07
• Subjects: Science -- Periodicals; Technology -- Periodicals; Patents -- United States -- Periodicals; 505
• DOI: 10.1016/j.jfranklin.2018.04.032
• Languages: English
• ISSNs: 0016-0032

Abstract

Abstract: This paper is concerned with the stability of discrete-time high-order neural networks (HONNs) with delays and impulses. Without applying the Lyapunov function, some sufficient conditions, which ensure the exponential stability and asymptotic stability of considered networks involving delays and impulses, are derived based on the fixed point theory. Finally, several numerical examples are given to demonstrate the effectiveness of the obtained results.