DocumentCode
3605107
Title
Asymptotic Stability of a Class of Neutral Delay Neuron System in a Critical Case
Author
Xiaofeng Liao ; Tingwen Huang
Author_Institution
Coll. of Electron. & Inf. Eng., Southwest Univ., Chongqing, China
Volume
26
Issue
12
fYear
2015
Firstpage
3320
Lastpage
3325
Abstract
In this brief, the asymptotic stability properties of a neutral delay neuron system are studied mainly in a critical case when the exponential stability is not possible. If a critical value of the coefficient in the neutral delay neuron system is considered, then the difficulty for our investigation is caused by the fact that the spectrum of the linear operator is asymptotically approximated to the imaginary axis. It is obvious that, in such a case, the equation is not exponentially stable, and one needs more subtle methods in order to characterize this type of asymptotic stability. Hence, first, the local asymptotic stability for the neutral delay neuron system is studied, and the main tools involved are the asymptotic expansions of characteristic roots, Laplace transforms, and function series, and a complete analysis of the stability diagram is also presented. Then, based on the energy method, the globally asymptotic stability results for the neutral delay neuron system are derived.
Keywords
Laplace transforms; approximation theory; asymptotic stability; delays; neurocontrollers; Laplace transform; asymptotic stability; function series; linear operator spectrum approximation; neutral delay neuron system; Asymptotic stability; Delays; Mathematical model; Neurons; Stability criteria; Thermal stability; Asymptotic stability; energy method; neuron system; neutral-type differential equations; nonexponential stability; nonexponential stability.;
fLanguage
English
Journal_Title
Neural Networks and Learning Systems, IEEE Transactions on
Publisher
ieee
ISSN
2162-237X
Type
jour
DOI
10.1109/TNNLS.2015.2469148
Filename
7229349
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