DocumentCode
816481
Title
Solving Quadratic Programming Problems by Delayed Projection Neural Network
Author
Yongqing Yang ; Jinde Cao
Author_Institution
Dept. of Math., Southeast Univ., Nanjing
Volume
17
Issue
6
fYear
2006
Firstpage
1630
Lastpage
1634
Abstract
In this letter, the delayed projection neural network for solving convex quadratic programming problems is proposed. The neural network is proved to be globally exponentially stable and can converge to an optimal solution of the optimization problem. Three examples show the effectiveness of the proposed network
Keywords
neural nets; quadratic programming; convex quadratic programming problems; delayed projection neural network; optimization problem; Artificial neural networks; Delay effects; Design engineering; Equations; Image converters; Lagrangian functions; Mathematics; Neural networks; Quadratic programming; Stability; Convex quadratic programming; delay; neural network; stability; Algorithms; Computer Simulation; Information Storage and Retrieval; Models, Statistical; Neural Networks (Computer); Pattern Recognition, Automated; Programming, Linear; Signal Processing, Computer-Assisted;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/TNN.2006.880579
Filename
4012050
Link To Document