Title :
Algebraic criteria for global exponential stability of cellular neural networks with multiple time delays
Author :
Liao, Xiao-xin ; Wang, Jun
Author_Institution :
Dept. of Control Sci. & Eng., Huazhong Univ. of Sci. & Technol., Hubei, China
fDate :
2/1/2003 12:00:00 AM
Abstract :
This brief presents three sufficient conditions for the global exponential stability of cellular neural networks with time delays. The new stability results provide algebraic criteria for stability verifications and improve upon existing ones with stronger conditions. To demonstrate the differences and features of the new stability criteria, several examples are discussed to compare the present results with the existing ones.
Keywords :
Lyapunov methods; asymptotic stability; cellular neural nets; delays; stability criteria; Lyapunov function; algebraic criteria; cellular neural networks; global exponential stability; multiple time delays; stability verifications; sufficient conditions; Cellular neural networks; Delay effects; Image processing; Lyapunov method; Neural networks; Nonlinear equations; Recurrent neural networks; Signal processing; Stability criteria; Sufficient conditions;
Journal_Title :
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
DOI :
10.1109/TCSI.2002.808213
