New Stability Criterion for Takagi‐Sugeno Fuzzy Cohen‐Grossberg Neural Networks with Probabilistic Time‐Varying Delays

Abstract

A new global asymptotic stability criterion of Takagi-Sugeno fuzzy Cohen-Grossberg neural networks with probabilistic timevarying delays was derived, in which the diffusion item can play its role. Owing to deleting the boundedness conditions on amplification functions, the main result is a novelty to some extent. Besides, there is another novelty in methods, for LyapunovKrasovskii functional is the positive definite form of powers, which is different from those of existing literature. Moreover, a numerical example illustrates the effectiveness of the proposed methods.

pth Moment Stability of a Stationary Solution for a Reaction Diffusion System with Distributed Delays

“…It is well known that, in practical engineering, electrons inevitably diffuse in the inhomogeneous electromagnetic field. In addition, hence, the stability analysis of the reaction-diffusion system has become a hot topic [1][2][3][4][5][6][7][8][9][10][11][12][13][14]. In recent decades, many authors, such as Linshan Wang, Qiankun Song and Jinde Cao, have studied the stability of Laplacian reaction-diffusion neural networks with time delay, and achieved fruitful results in Laplacian diffusion systems [7][8][9][10][11][12][13][14].…”