Further stability analysis on Cohen–Grossberg neural networks with time-varying and distributed delays
Further stability analysis on Cohen–Grossberg neural networks with time-varying and distributed delays
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DOI：
10.1080/00207720903576514
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发表时间：
2011-10
影响因子：
4.3
通讯作者：
Tao Li;Aiguo Song;S. Fei
中科院分区：
文献类型：
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作者：
Tao Li;Aiguo Song;S. Fei
本文关注的是具有间隔时变 (0 ≤ τ0 ≤ τ(t) ≤ τ m ) 和分布式延迟的 Cohen-Grossberg 神经网络的渐近稳定性，其中处理两种类型的分布式延迟：一种是有界的，另一种是无界的。通过划分延迟区间[0, τ0]和[τ0, τ m ]，并选择两个增广Lyapunov-Krasovskii泛函，利用简化的自由权矩阵法和凸组合，得到了保证全局稳定性的充分条件。这些稳定性标准以线性矩阵不等式 (LMI) 的形式表示，并且可以通过使用 Matlab 工具箱中的 LMI 轻松检查。最后，给出了三个数值例子来说明理论结果的有效性和减少的保守性。
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.