Attractability and location of equilibrium point of cellular neural networks with time-varying delays.
This paper presents new theoretical results on global exponential stability of cellular neural networks with time-varying delays. The stability conditions depend on external inputs, connection weights and delays of cellular neural networks. Using these results, global exponential stability of cellular neural networks can be derived, and the estimate for location of equilibrium point can also be obtained. Finally, the simulating results demonstrate the validity and feasibility of our proposed approach.
Zeng
Zhigang
Z
Department of Automation, University of Science and Technology of China, Hefei, Anhui 230026, China. zhigangzeng@iim.ac.cn
Huang
De-Shuang
DS
Wang
Zengfu
Z
D000818:Animals; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology*; D011930:Reaction Time / Q000502:physiology; D013997:Time Factors