A new delayed projection neural network for solving quadratic programming problems subject to linear constraints

In this paper, a new projection neural network with two time delays is proposed for solving quadratic programming problems subject to linear constraints. And we give the existence of the continuous solution. By the theory of functional differential equation, the proposed neural network is proved to...

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Bibliographic Details
Published inApplied mathematics and computation Vol. 219; no. 6; pp. 3139 - 3146
Main Authors Niu, Jiuxiao, Liu, Deyou
Format Journal Article
LanguageEnglish
Published Elsevier Inc 25.11.2012
Subjects
Computation
Computer simulation
Differential equations
Globally exponentially stable
Linear constraints
Mathematical models
Neural networks
Projection
Projection neural networks
Quadratic programming
Time delay
Time delays
Time delays
Globally exponentially stable
Projection neural networks
Quadratic programming
Linear constraints
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Summary:In this paper, a new projection neural network with two time delays is proposed for solving quadratic programming problems subject to linear constraints. And we give the existence of the continuous solution. By the theory of functional differential equation, the proposed neural network is proved to be globally exponentially stable under some conditions. Simulation results with some applications show the performance and characteristic of the proposed neural network.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0096-3003
1873-5649
DOI:10.1016/j.amc.2012.09.047