Multistability of Recurrent Neural Networks With Time-varying Delays and the Piecewise Linear Activation Function

Author

Zeng, Zhigang ; Huang, Tingwen ; Zheng, Wei Xing

Author_Institution

Dept. of Control Sci. & Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China

Volume

21

Issue

8

fYear

2010

Firstpage

1371

Lastpage

1377

Abstract

In this brief, stability of multiple equilibria of recurrent neural networks with time-varying delays and the piecewise linear activation function is studied. A sufficient condition is obtained to ensure that n-neuron recurrent neural networks can have (4k-1)n equilibrium points and (2k)n of them are locally exponentially stable. This condition improves and extends the existing stability results in the literature. Simulation results are also discussed in one illustrative example.

Keywords

delays; piecewise linear techniques; recurrent neural nets; exponential stability; piecewise linear activation function; recurrent neural network multistability; time-varying delays; Associative memory; Biological neural networks; Brain modeling; Control engineering education; Educational institutions; Orbits; Piecewise linear techniques; Recurrent neural networks; Stability; Sufficient conditions; Attractive set; multistability; piecewise linear; time-varying delays; Algorithms; Animals; Artificial Intelligence; Brain; Humans; Linear Models; Mathematical Concepts; Memory; Nerve Net; Neural Networks (Computer); Neurons; Reaction Time; Time Factors;

fLanguage

English

Journal_Title

Neural Networks, IEEE Transactions on

Publisher

ieee

ISSN

1045-9227

Type

jour

DOI

10.1109/TNN.2010.2054106

Filename

5508438