DocumentCode
1940769
Title
Stability of Cohen-Grossberg Neural Networks with Nonnegative Periodic solutions
Author
Chen, Tianping ; Bai, Yanchun
Author_Institution
Arizona State Univ., Tempe
fYear
2007
fDate
12-17 Aug. 2007
Firstpage
242
Lastpage
247
Abstract
In this paper, we discuss nonnegative periodic solutions for generalized Cohen-Grossberg neural networks. Without assuming strict positivity and boundedness of the amplification functions, the dynamics of periodic Cohen-Grossberg neural networks are studied. By applying a direct method, sufficient conditions guaranteeing the existence and global asymptotic stability of nonnegative periodic solution are derived. Also the criterion does not depend on the assumption for amplification functions being upper and low bounded or the external inputs.
Keywords
asymptotic stability; functions; neural nets; Cohen-Grossberg neural networks; amplification functions; global asymptotic stability; nonnegative periodic solutions; periodic neural networks; Associative memory; Asymptotic stability; Delay systems; Neural networks; Pattern recognition; Signal processing; Sufficient conditions; Time measurement; Time varying systems; USA Councils;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location
Orlando, FL
ISSN
1098-7576
Print_ISBN
978-1-4244-1379-9
Electronic_ISBN
1098-7576
Type
conf
DOI
10.1109/IJCNN.2007.4370962
Filename
4370962
Link To Document