Robust stability of Cohen-Grossberg neural networks via state transmission matrix.
This brief is concerned with the global robust exponential stability of a class of interval Cohen-Grossberg neural networks with both multiple time-varying delays and continuously distributed delays. Some new sufficient robust stability conditions are established in the form of state transmission matrix, which are different from the existing ones. Furthermore, a sufficient condition is also established to guarantee the global stability for this class of Cohen-Grossberg neural networks without uncertainties. Three examples are used to show the effectiveness of the obtained results.
Wang
Zhanshan
Z
School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110004, China. zhanshan_wang@163.com
Zhang
Huaguang
H
Yu
Wen
W
D000465:Algorithms; D016571:Neural Networks, Computer; D013997:Time Factors