BI-DIRECTIONAL COHEN-GROSSBERG NEURAL NETWORK WITH DISCRETE TIME

• 来源期刊: 微分方程年刊：英文版
• 学科: 数学
• 年，卷（期）: 2009,（1）
• 页数: 1页
• 分类号: O175

摘要

Discrete-time version of the bi-directional Cohen-Grossberg neural network is stud-ied in this paper. Some sufficient conditions are obtained to ensure the global exponen-tial stability of such networks with discrete time based on Lyapunov method. These results do not require the symmetry of the connection matrix and the monotonicity, boundedness and differentiability of the activation function.