Title: New stochastic synchronisation condition of neutral-type Markovian chaotic neural networks under impulsive perturbations

Authors: Cheng-De Zheng; He-He Jia; Qihe Shan

Addresses: School of Science, Dalian Jiaotong University, Dalian, 116028, China ' School of Electrical Information, Dalian Jiaotong University, Dalian, 116028, China ' Navigation College, Dalian Maritime University, Dalian, 116026, China

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.

Keywords: 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.

DOI: 10.1504/IJICA.2019.102113

International Journal of Innovative Computing and Applications, 2019 Vol.10 No.2, pp.100 - 106

Received: 04 Sep 2018
Accepted: 29 Dec 2018
Published online: 06 Sep 2019 *

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