指数稳定性
指数函数
趋同(经济学)
人工神经网络
收敛速度
数学
应用数学
指数增长
理论(学习稳定性)
计算机科学
数学分析
人工智能
物理
非线性系统
机器学习
钥匙(锁)
计算机安全
经济
量子力学
经济增长
作者
Yi Zhang,P.A. Heng,A.W.-C. Fu
摘要
Estimate of exponential convergence rate and exponential stability are studied for a class of neural networks which includes the Hopfield neural networks and the cellular neural networks. Both local and global exponential convergence is discussed. Theorems for estimate of exponential convergence rate are established and the bounds on the rate of convergence are given. The domains of attraction in the case of local exponential convergence are obtained. Simple conditions are presented for checking exponential stability of the neural networks.
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