Solution of Linear Programming Problems using a Neural Network with Non-Linear Feedback
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Date
2012-12
Authors
Rahman, Syed Atiqur
Ansari, Mohd. Samar
Moinuddin, Athar Ali
ORCID
Advisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
Publisher
Společnost pro radioelektronické inženýrství
Abstract
This paper presents a recurrent neural circuit for solving linear programming problems. The objective is to minimize a linear cost function subject to linear constraints. The proposed circuit employs non-linear feedback, in the form of unipolar comparators, to introduce transcendental terms in the energy function ensuring fast convergence to the solution. The proof of validity of the energy function is also provided. The hardware complexity of the proposed circuit compares favorably with other proposed circuits for the same task. PSPICE simulation results are presented for a chosen optimization problem and are found to agree with the algebraic solution. Hardware test results for a 2–variable problem further serve to strengthen the proposed theory.
Description
Citation
Radioengineering. 2012, vol. 21, č. 4, s. 1171-1177. ISSN 1210-2512
http://www.radioeng.cz/fulltexts/2012/12_04_1171_1177.pdf
http://www.radioeng.cz/fulltexts/2012/12_04_1171_1177.pdf
Document type
Peer-reviewed
Document version
Published version
Date of access to the full text
Language of document
en