DocumentCode :
592386
Title :
An algorithm for fast constrained nuclear norm minimization and applications to systems identification
Author :
Ayazoglu, Mustafa ; Sznaier, M.
Author_Institution :
Dept. of Electr. & Comput. Eng., Northeastern Univ., Boston, MA, USA
fYear :
2012
fDate :
10-13 Dec. 2012
Firstpage :
3469
Lastpage :
3475
Abstract :
This paper presents a novel algorithm for efficiently minimizing the nuclear norm of a matrix subject to structural and semi-definite constraints. It requires performing only thresholding and eigenvalue decomposition steps and converges Q-superlinearly to the optimum. Thus, this algorithm offers substantial advantages, both in terms of memory requirements and computational time over conventional semi-definite programming solvers. These advantages are illustrated using as an example the problem of finding the lowest order system that interpolates a collection of noisy measurements.
Keywords :
eigenvalues and eigenfunctions; identification; interpolation; mathematical programming; matrix algebra; minimisation; reduced order systems; Q-superlinear convergence; computational time; eigenvalue decomposition; fast constrained nuclear norm minimization; interpolation; lowest order system; matrix subject; memory requirement; noisy measurement; semidefinite constraint; semidefinite programming; structural constraint; system identification; thresholding; Computational modeling; Eigenvalues and eigenfunctions; Minimization; Noise; Noise measurement; Optimization; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
Conference_Location :
Maui, HI
ISSN :
0743-1546
Print_ISBN :
978-1-4673-2065-8
Electronic_ISBN :
0743-1546
Type :
conf
DOI :
10.1109/CDC.2012.6426520
Filename :
6426520
Link To Document :
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