New stochastic synchronisation condition of neutral-type Markovian chaotic neural networks under impulsive perturbations. (2nd September 2019)

• Record Type: Journal Article
• Authors: Zheng, Cheng-De; Jia, He-He; Shan, Qihe
• Is Part Of: International journal of innovative computing and applications. Volume 10:Number 2(2019)
• Page Start: 100
• Page End: 106
• Publication Date: 2019-09-02
• Subjects: stochastically asymptotic synchronisation -- Markovian jump -- chaotic neural networks -- impulse -- reciprocal convex -- innovative computing -- neutral-type -- MATLAB -- activation functions -- Lyapunov functional method -- free-weight matrix method -- drive-response concept -- Jensen integral inequality; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

Abstract

This paper investigates the globally stochastic synchronisation problem for a class of neutral-type chaotic neural networks with Markovian jumping parameters under impulsive perturbations in mean square. By virtue of drive-response concept and time-delay feedback control techniques, by using the Lyapunov functional method, vector Wirtinger-type inequality, a novel reciprocal convex lemma and the free-weight matrix method, a novel sufficient condition is derived to ensure the asymptotic synchronisation of two identical Markovian jumping chaotic delayed neural networks with impulsive perturbation. The proposed results, which do not require the differentiability and monotonicity of the activation functions, can be easily checked via MATLAB software. Finally, a numerical example with simulations is provided to illustrate the effectiveness of the presented synchronisation scheme.