DocumentCode
1365586
Title
New sufficient conditions for absolute stability of neural networks
Author
Liang, Xue-Bin ; Wu, Li-De
Author_Institution
Dept. of Comput. Sci., Fudan Univ., Shanghai, China
Volume
45
Issue
5
fYear
1998
fDate
5/1/1998 12:00:00 AM
Firstpage
584
Lastpage
586
Abstract
The main result obtained in this paper is that for a neural network with interconnection matrix T, if -T is quasi-diagonally row-sum or column-sum dominant, then the network system is absolutely stable. The above two sufficient conditions for absolute stability are independent of the existing sufficient ones in the literature. Under either of the above two sufficient conditions for absolute stability, the vector field defined by the network system is also structurally stable
Keywords
absolute stability; neural nets; absolute stability; interconnection matrix; neural network; structural stability; sufficient conditions; vector field; Circuits; Computer science; Differential equations; Eigenvalues and eigenfunctions; Neural networks; Neurons; Stability; Structural engineering; Sufficient conditions; Symmetric matrices;
fLanguage
English
Journal_Title
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
Publisher
ieee
ISSN
1057-7122
Type
jour
DOI
10.1109/81.668873
Filename
668873
Link To Document