Further stability analysis on Cohen–Grossberg neural networks with time-varying and distributed delays

Abstract

The article is concerned with asymptotical stability for Cohen-Grossberg neural networks with both interval time-varying (0 0 (t) m ) and distributed delays, in which two types of distributed delays are treated: one is bounded while the other is unbounded. Through partitioning the delay intervals [0, 0 ] and [ 0 , m ], and choosing two augmented Lyapunov-Krasovskii functionals, some sufficient conditions are obtained to guarantee the global stability by employing the simplified free-weighting matrix method and convex combination. These stability criteria are presented in terms of linear matrix inequalities (LMIs) and can be easily checked by resorting to LMI in Matlab toolbox. Finally, three numerical examples are given to illustrate the effectiveness and reduced conservatism of the theoretical results.

Almost Automorphic Solutions for Fuzzy Cohen-Grossberg Neural Networks with Mixed Time Delays

“…Some models such as Hopfield-type neural networks, CNNs, BAM-type models are special cases of Cohen-Grossberg neural networks. For more details about Cohen-Grossberg neural networks, one can see, for example, [7][8][9][10][11][12].…”