Title :
Stability analysis of multiple equilibria for recurrent neural networks with time-varying delays
Author :
Zhigang Zeng ; Wei Xing Zheng
Author_Institution :
Dept. of Control Sci. & Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
Abstract :
The problem of stability of multiple equilibria is studied in this paper for two kinds of recurrent neural networks with time-varying delays and activation functions symmetrical with respect to the origin on the phase plane. Some sufficient conditions are obtained to ensure that two kinds of recurrent neural networks can have (2m + 1)n equilibrium points and (m + 1)n of them are locally exponentially stable. The derived conditions are valuable extensions to the existing results on stability of multiple equilibria for recurrent neural networks with time-varying delays in the literature.
Keywords :
asymptotic stability; delays; recurrent neural nets; time-varying systems; transfer functions; activation functions; exponential stability; multiple equilibria; phase plane; recurrent neural networks; stability analysis; time-varying delays; Bismuth; Cellular neural networks; Delays; Recurrent neural networks; Stability analysis; Vectors;
Conference_Titel :
Circuits and Systems (ISCAS), 2013 IEEE International Symposium on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-5760-9
DOI :
10.1109/ISCAS.2013.6572288
