Reachable set estimation for Markovian jump neural networks with time-varying delay. (December 2018)

• Record Type: Journal Article
• Authors: Lin, Wen-Juan; He, Yong; Wu, Min; Liu, Qingping
• Is Part Of: Neural networks. Volume 108(2018)
• Page Start: 527
• Page End: 532
• Publication Date: 2018-12
• Subjects: Markovian jump neural networks -- Time-varying delay -- Reachable set estimation -- Lyapunov–Krasovskii functional; Neural computers -- Periodicals; Neural networks (Computer science) -- Periodicals; Neural networks (Neurobiology) -- Periodicals; Nervous System -- Periodicals; Ordinateurs neuronaux -- Périodiques; Réseaux neuronaux (Informatique) -- Périodiques; Réseaux neuronaux (Neurobiologie) -- Périodiques; Neural computers; Neural networks (Computer science); Neural networks (Neurobiology); Periodicals; 006.32
• DOI: 10.1016/j.neunet.2018.09.011
• Languages: English
• ISSNs: 0893-6080

Abstract

Abstract: This paper is concerned with the reachable set estimation for Markovian jump neural networks with time-varying delay and bounded peak inputs. The objective is to find a description of a reachable set that is containing all reachable states starting from the origin. In the framework of Lyapunov–Krasovskii functional method, an appropriate Lyapunov–Krasovskii functional is constructed firstly. Then by using the Wirtinger-based integral inequality and the extended reciprocally convex matrix inequality, an ellipsoidal description of the reachable set for the considered neural networks is derived. Finally, a numerical example with simulation results is provided to verify the effectiveness of our results.