DocumentCode
1133512
Title
Recurrent neural network for solving quadratic programming problems with equality constraints
Author
Wang, Jiacheng
Author_Institution
North Dakota Univ., Grand Forks, ND, USA
Volume
28
Issue
14
fYear
1992
fDate
7/2/1992 12:00:00 AM
Firstpage
1345
Lastpage
1347
Abstract
A recurrent neural network for solving quadratic programming problems with equality constraints is presented. The proposed recurrent neural network is asymptotically stable and able to generate optimal solutions to quadratic programs with equality constraints. An opamp based analogue circuit realisation of the recurrent neural network is described. An illustrative example is also discussed to demonstrate the performance and characteristics of the analogue neural network.
Keywords
analogue computer circuits; neural nets; operational amplifiers; quadratic programming; asymptotically stable; equality constraints; opamp based analogue circuit realisation; optimal solutions; quadratic programming problems; recurrent neural network;
fLanguage
English
Journal_Title
Electronics Letters
Publisher
iet
ISSN
0013-5194
Type
jour
DOI
10.1049/el:19920854
Filename
149397
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