International Journal of Computational Intelligence Systems

Volume 7, Issue 4, August 2014, Pages 724 - 732

Analysis and Application of A One-Layer Neural Network for Solving Horizontal Linear Complementarity Problems

Authors
Xingbao Gao, Jing Wang
Corresponding Author
Xingbao Gao
Available Online 1 August 2014.
DOI
https://doi.org/10.1080/18756891.2013.858903How to use a DOI?
Keywords
Horizontal linear complementarity problem, neural network, stability, application
Abstract
In this paper, we analyze the stability and convergence of a one-layer neural network proposed by Gao and Wang, which is designed to solve a class of horizontal linear complementarity problems. The globally asymptotical stability and globally exponential stability of this network are proved strictly under mild conditions, respectively. Meanwhile, this network is applied to solve a transportation problem and a class of the absolute equations.
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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
7 - 4
Pages
724 - 732
Publication Date
2014/08
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
https://doi.org/10.1080/18756891.2013.858903How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - JOUR
AU  - Xingbao Gao
AU  - Jing Wang
PY  - 2014
DA  - 2014/08
TI  - Analysis and Application of A One-Layer Neural Network for Solving Horizontal Linear Complementarity Problems
JO  - International Journal of Computational Intelligence Systems
SP  - 724
EP  - 732
VL  - 7
IS  - 4
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2013.858903
DO  - https://doi.org/10.1080/18756891.2013.858903
ID  - Gao2014
ER  -