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 :
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