Robust H∞ filtering for Markovian jumping static neural networks with time-varying delays. (June 2020)

• Record Type: Journal Article
• Authors: Zhao, Aodong; Zhang, Nan; Xi, Maolong; Sun, Jun; Dong, Meiyan
• Is Part Of: Journal of algorithms & computational technology. Volume 14(2020)
• Publication Date: 2020-06
• Subjects: H∞ filtering Markovian jumping -- static neural networks -- Wirtinger inequalities; Computer algorithms -- Periodicals; Numerical calculations -- Periodicals; Computer algorithms; Numerical calculations; Periodicals; 518.1
• DOI: 10.1177/1748302620931340
• Languages: English
• ISSNs: 1748-3018

Abstract

The problem of robust H ∞ filtering for Markovian jumping static neural networks with time-varying delays is considered in this paper. The effect of the activation function on the time delays is comprehensively considered. Based on Wirtinger inequality, a new inequality is quoted to solve the Lyapunov functions with the double-integral terms. Then, a less conservative result on the robust H ∞ filtering is obtained, which guarantees the resulting error systems stochastically stable and satisfies a prescribed H ∞ performance index. The effectiveness of the developed results is finally demonstrated by numerical examples.