Conjugate Gradient Algorithm for Optimization under Unitary Matrix Constraint

In this paper we introduce a Riemannian algorithm for minimizing (or maximizing) a real-valued function J of complex-valued matrix argument W under the constraint that W is an n×n unitary matrix. This type of constrained optimization problem arises in many array and multi-channel signal processing a...

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Main Authors: Abrudan, T, Eriksson, J, Koivunen, V
Format: Journal article
Published: 2015
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author Abrudan, T
Eriksson, J
Koivunen, V
author_facet Abrudan, T
Eriksson, J
Koivunen, V
author_sort Abrudan, T
collection OXFORD
description In this paper we introduce a Riemannian algorithm for minimizing (or maximizing) a real-valued function J of complex-valued matrix argument W under the constraint that W is an n×n unitary matrix. This type of constrained optimization problem arises in many array and multi-channel signal processing applications. We propose a conjugate gradient (CG) algorithm on the Lie group of unitary matrices U(n). The algorithm fully exploits the group properties in order to reduce the computational cost. Two novel geodesic search methods exploiting the almost periodic nature of the cost function along geodesics on U(n) are introduced. We demonstrate the performance of the proposed CG algorithm in a blind signal separation application. Computer simulations show that the proposed algorithm outperforms other existing algorithms in terms of convergence speed and computational complexity.
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spelling oxford-uuid:689e48e4-76f3-4fd3-8b3b-30752d8ef77d2022-03-26T18:45:59ZConjugate Gradient Algorithm for Optimization under Unitary Matrix ConstraintJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:689e48e4-76f3-4fd3-8b3b-30752d8ef77dDepartment of Computer Science2015Abrudan, TEriksson, JKoivunen, VIn this paper we introduce a Riemannian algorithm for minimizing (or maximizing) a real-valued function J of complex-valued matrix argument W under the constraint that W is an n×n unitary matrix. This type of constrained optimization problem arises in many array and multi-channel signal processing applications. We propose a conjugate gradient (CG) algorithm on the Lie group of unitary matrices U(n). The algorithm fully exploits the group properties in order to reduce the computational cost. Two novel geodesic search methods exploiting the almost periodic nature of the cost function along geodesics on U(n) are introduced. We demonstrate the performance of the proposed CG algorithm in a blind signal separation application. Computer simulations show that the proposed algorithm outperforms other existing algorithms in terms of convergence speed and computational complexity.
spellingShingle Abrudan, T
Eriksson, J
Koivunen, V
Conjugate Gradient Algorithm for Optimization under Unitary Matrix Constraint
title Conjugate Gradient Algorithm for Optimization under Unitary Matrix Constraint
title_full Conjugate Gradient Algorithm for Optimization under Unitary Matrix Constraint
title_fullStr Conjugate Gradient Algorithm for Optimization under Unitary Matrix Constraint
title_full_unstemmed Conjugate Gradient Algorithm for Optimization under Unitary Matrix Constraint
title_short Conjugate Gradient Algorithm for Optimization under Unitary Matrix Constraint
title_sort conjugate gradient algorithm for optimization under unitary matrix constraint
work_keys_str_mv AT abrudant conjugategradientalgorithmforoptimizationunderunitarymatrixconstraint
AT erikssonj conjugategradientalgorithmforoptimizationunderunitarymatrixconstraint
AT koivunenv conjugategradientalgorithmforoptimizationunderunitarymatrixconstraint