In this paper, we study Cohen-Grossberg neural networks （CGNN） with time-varying delay. Based on Halanay inequality and continuation theorem of the coincidence degree, we obtain some sufficient conditions ensuring t...In this paper, we study Cohen-Grossberg neural networks （CGNN） with time-varying delay. Based on Halanay inequality and continuation theorem of the coincidence degree, we obtain some sufficient conditions ensuring the existence, uniqueness, and global exponential stability of periodic solution. Our results complement previously known results.展开更多
基金Supported by the National Natural Science Foundation of China (No. 11071060)Key Program of Application Science Foundation of Hunan Province (No. 2008FJ2008)
文摘In this paper, we study Cohen-Grossberg neural networks （CGNN） with time-varying delay. Based on Halanay inequality and continuation theorem of the coincidence degree, we obtain some sufficient conditions ensuring the existence, uniqueness, and global exponential stability of periodic solution. Our results complement previously known results.
