Optimization algorithms exploiting unitary constraints

This paper presents novel algorithms that iteratively converge to a local minimum of a real-valued function f (X) subject to the constraint that the columns of the complex-valued matrix X are mutually orthogonal and have unit norm. The algorithms are derived by reformulating the constrained optimiza...

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Bibliographic Details
Published in:	IEEE transactions on signal processing Vol. 50; no. 3; pp. 635 - 650
Main Author:	Manton, J.H.
Format:	Journal Article
Language:	English
Published:	New York, NY IEEE 01.03.2002 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Applied sciences Constraint optimization Cost function Eigenvalues Eigenvalues and eigenfunctions Eigenvectors Exact sciences and technology Frequency estimation Information, signal and communications theory Iterative algorithms Manifolds Mathematical analysis Mathematical methods Norms Operational research and scientific management Operational research. Management science Optimization Optimization. Search problems Signal processing Signal processing algorithms Space technology Subspace constraints Symmetric matrices Telecommunications and information theory Performance evaluation Simulation Steepest descent method Convergence rate Signal processing Eigenvalue problem Algorithm Newton method Constrained optimization
ISSN:	1053-587X, 1941-0476
Online Access:	Get full text
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