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Publish place: Caspian Journal of Mathematical Sciences، Vol: 4، Issue: 2
Publish Year: 1394
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_CJMS-4-2_006
تاریخ نمایه سازی: 16 مهر 1398
Abstract:
In this paper we solve a wide rang of Semidefinite Programming (SDP) Problem by using Recurrent Neural Networks (RNNs).
SDP is an important numerical tool for analysis and synthesis in systems and control theory. First we reformulate the problem to a linear programming problem, second we reformulate it to a first order system of ordinary differential equations.
Then a recurrent neural network model is proposed to compute related primal and dual solutions simultaneously.Illustrative examples are included to demonstrate the validity and applicability of the technique.
Authors
S. M. Mirhosseini Alizamini
Department of Mathematics, Payame Noor University, Tehran, Iran
A. Malek
Department of Applied Mathematics, faculty of Mathematical Sciences,Tarbiat Modares University, Tehrasn, Iran
Gh. Ahmadi
Department of Mathematics, Payame Noor University, Tehran, Iran