DocumentCode :
1648491
Title :
Design and implementation of a parser/solver for SDPs with matrix structure
Author :
Wu, Shao-Po ; Boyd, Stephen
Author_Institution :
Dept. of Electr. Eng., Stanford Univ., CA, USA
fYear :
1996
Firstpage :
240
Lastpage :
245
Abstract :
A wide variety of analysis and design problems arising in control communication and information theory, statistics, computational geometry and many other fields can be expressed as semidefinite programming problems (SDPs) or determinant maximization problems (maxdet-problems). In engineering applications these problems usually have matrix structure, i.e., the optimization variables are matrices. Recent interior-point methods can exploit such structure to gain huge efficiency. In this paper, we describe the design and implementation of a parser/solver for SDPs and maxdet-problems with matrix structure. The parser/solver parses a problem specification close to its natural mathematical description, solves the compiled problem efficiently, and returns the results in a convenient form
Keywords :
grammars; linear programming; mathematics computing; matrix algebra; specification languages; determinant maximization; engineering problems; interior-point methods; matrix inequality; matrix structure; maxdet-problems; optimization; parser; semidefinite programming; solver; specification language; Complexity theory; Computational geometry; Eigenvalues and eigenfunctions; Linear matrix inequalities; Matrix converters; Symmetric matrices;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer-Aided Control System Design, 1996., Proceedings of the 1996 IEEE International Symposium on
Conference_Location :
Dearborn, MI
Print_ISBN :
0-7803-3032-3
Type :
conf
DOI :
10.1109/CACSD.1996.555290
Filename :
555290
Link To Document :
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