DocumentCode
3583364
Title
Novel global exponential stability criterion for BAM neural networks with time-varying delays
Author
Wang, Fen ; Wu, Huaiyu
Author_Institution
Coll. of Inf. Sci. & Eng., Wuhan Univ. of Sci. & Technol., Wuhan, China
Volume
3
fYear
2010
Firstpage
1126
Lastpage
1130
Abstract
This paper concerns with the uniqueness and global exponential stability of the equilibrium point of BAM neural networks with time-varying delays. By applying M-matrix theory, inequality technique and reduction to absurdity, sufficient conditions are obtained. A numerical example is provided to illustrate the effectiveness of the obtained results.
Keywords
asymptotic stability; content-addressable storage; matrix algebra; neural nets; time-varying systems; BAM neural network; M-matrix theory; bidirectional associative memory; equilibrium point; global exponential stability; inequality technique; time-varying delay; Artificial neural networks; Associative memory; Asymptotic stability; Delay; Numerical stability; Stability criteria; Bidirectional associative memory (BAM) neural networks; Delay; Global exponential stability;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2010 Sixth International Conference on
Print_ISBN
978-1-4244-5958-2
Type
conf
DOI
10.1109/ICNC.2010.5583681
Filename
5583681
Link To Document