Title :
New Exponential Stability Criteria for Delayed Neural Networks
Author :
Li, Chuandong ; Liao, Xiaofeng
Author_Institution :
Coll. of Comput. Sci. & Eng., Chongqing Univ.
Abstract :
Several new criteria for the exponential stability of delayed neural networks (DNNs) and its corresponding convergence degrees are presented. The proposed criteria do not require that the activation functions are continuous and bounded, and therefore are less restricted and less conservative
Keywords :
asymptotic stability; convergence; delay systems; neural nets; stability criteria; transfer functions; activation functions; convergence degrees; delayed neural networks; exponential stability criteria; Delay effects; Educational institutions; Hydrogen; Linear matrix inequalities; Lyapunov method; Neural networks; Neurofeedback; Neurons; Stability criteria; Symmetric matrices; Delayed neural network; Exponential stability; Lyapunov function; Time delays;
Conference_Titel :
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9422-4
DOI :
10.1109/ICNNB.2005.1614593
