Further stability analysis on Cohen–Grossberg neural networks with time-varying and distributed delays
Tao Li, Aiguo Song, Shumin Fei · International Journal of Systems Science · 2010
The article is concerned with asymptotical stability for Cohen–Grossberg neural networks with both interval time-varying (0 ≤ τ0 ≤ τ(t) ≤ τ 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, τ0] and [τ0, τ 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.