Title :
Asymptotically behavior of cellular neural networks with time delays
Author_Institution :
Dept. of Math., Chongqing Educ. Coll., Chongqing, China
Abstract :
In this paper, some sufficient conditions of the asymptotically stability for cellular neural networks are obtained by the properties of the Lozinskii measures and techniques of differential inequalities, and the boundedness of nonlinear activation functions is not required.
Keywords :
asymptotic stability; cellular neural nets; delays; nonlinear functions; Lozinskii measures; asymptotically stability; cellular neural networks; differential inequalities; nonlinear activation functions; time delays; Artificial neural networks; Asymptotic stability; Cellular neural networks; Delay; Delay effects; Numerical stability; Stability analysis; Asymptotically stably; Cellular neural network; Lozinskii measures; M-matrix;
Conference_Titel :
Control Conference (CCC), 2011 30th Chinese
Conference_Location :
Yantai
Print_ISBN :
978-1-4577-0677-6
Electronic_ISBN :
1934-1768
