Title :
Global Asymptotic Stability of Delayed Cellular Neural Networks
Author :
Zhang, Huaguang ; Wang, Zhanshan
Author_Institution :
Northeastern Univ., Liaoning
fDate :
5/1/2007 12:00:00 AM
Abstract :
A new criterion for the global asymptotic stability of the equilibrium point of cellular neural networks with multiple time delays is presented. The obtained result possesses the structure of a linear matrix inequality and can be solved efficiently using the recently developed interior-point algorithm. A numerical example is used to show the effectiveness of the obtained result
Keywords :
asymptotic stability; cellular neural nets; linear matrix inequalities; delayed cellular neural networks; global asymptotic stability; interior-point algorithm; linear matrix inequality; multiple time delays; Asymptotic stability; Cellular neural networks; Delay effects; Educational institutions; Image processing; Linear matrix inequalities; Neural networks; Nonlinear equations; Signal processing algorithms; Sufficient conditions; Cellular neural networks; global asymptotic stability; multiple time delays;
Journal_Title :
Neural Networks, IEEE Transactions on
DOI :
10.1109/TNN.2007.891628
