Matrix function optimization under weighted boundary constraints and its applications in network control

The matrix function optimization under weighted boundary constraints on the matrix variables is investigated in this work. An "index-notation-arrangement based chain rule" (I-Chain rule) is introduced to obtain the gradient of a matrix function. By doing this, we propose the weighted trace...

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Main Authors: Tang, Pei, Li, Guoqi, Ma, Chen, Wang, Ran, Xiao, Gaoxi, Shi, Luping
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2020
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Online Access:https://hdl.handle.net/10356/142715
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1427152020-06-29T02:13:54Z Matrix function optimization under weighted boundary constraints and its applications in network control Tang, Pei Li, Guoqi Ma, Chen Wang, Ran Xiao, Gaoxi Shi, Luping School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Matrix Function Optimization Matrix Variable The matrix function optimization under weighted boundary constraints on the matrix variables is investigated in this work. An "index-notation-arrangement based chain rule" (I-Chain rule) is introduced to obtain the gradient of a matrix function. By doing this, we propose the weighted trace-constraint-based projected gradient method (WTPGM) and weighted orthornormal-constraint-based projected gradient method (WOPGM) to locate a point of minimum of an objective/cost function of matrix variables iteratively subject to weighted trace constraint and weighted orthonormal constraint, respectively. New techniques are implemented to establish the convergence property of both algorithms. In addition, compared with the existing scheme termed "orthornormal-constraint-based projected gradient method" (OPGM) that requires the gradient has to be represented by the multiplication of a symmetrical matrix and the matrix variable itself, such a condition has been relaxed in WOPGM. Simulation results show the effectiveness of our methods not only in network control but also in other learning problems. We believe that the results reveal interesting physical insights in the field of network control and allow extensive applications of matrix function optimization problems in science and engineering. MOE (Min. of Education, S’pore) 2020-06-29T02:13:54Z 2020-06-29T02:13:54Z 2018 Journal Article Tang, P., Li, G., Ma, C., Wang, R., Xiao, G., & Shi, L. (2018). Matrix function optimization under weighted boundary constraints and its applications in network control. ISA transactions, 80, 232-243. doi:10.1016/j.isatra.2018.06.010 0019-0578, https://hdl.handle.net/10356/142715 10.1016/j.isatra.2018.06.010 30037531 2-s2.0-85050088274 80 232 243 en ISA transactions © 2018 ISA. All rights reserved.
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Matrix Function Optimization
Matrix Variable
spellingShingle Engineering::Electrical and electronic engineering
Matrix Function Optimization
Matrix Variable
Tang, Pei
Li, Guoqi
Ma, Chen
Wang, Ran
Xiao, Gaoxi
Shi, Luping
Matrix function optimization under weighted boundary constraints and its applications in network control
description The matrix function optimization under weighted boundary constraints on the matrix variables is investigated in this work. An "index-notation-arrangement based chain rule" (I-Chain rule) is introduced to obtain the gradient of a matrix function. By doing this, we propose the weighted trace-constraint-based projected gradient method (WTPGM) and weighted orthornormal-constraint-based projected gradient method (WOPGM) to locate a point of minimum of an objective/cost function of matrix variables iteratively subject to weighted trace constraint and weighted orthonormal constraint, respectively. New techniques are implemented to establish the convergence property of both algorithms. In addition, compared with the existing scheme termed "orthornormal-constraint-based projected gradient method" (OPGM) that requires the gradient has to be represented by the multiplication of a symmetrical matrix and the matrix variable itself, such a condition has been relaxed in WOPGM. Simulation results show the effectiveness of our methods not only in network control but also in other learning problems. We believe that the results reveal interesting physical insights in the field of network control and allow extensive applications of matrix function optimization problems in science and engineering.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Tang, Pei
Li, Guoqi
Ma, Chen
Wang, Ran
Xiao, Gaoxi
Shi, Luping
format Article
author Tang, Pei
Li, Guoqi
Ma, Chen
Wang, Ran
Xiao, Gaoxi
Shi, Luping
author_sort Tang, Pei
title Matrix function optimization under weighted boundary constraints and its applications in network control
title_short Matrix function optimization under weighted boundary constraints and its applications in network control
title_full Matrix function optimization under weighted boundary constraints and its applications in network control
title_fullStr Matrix function optimization under weighted boundary constraints and its applications in network control
title_full_unstemmed Matrix function optimization under weighted boundary constraints and its applications in network control
title_sort matrix function optimization under weighted boundary constraints and its applications in network control
publishDate 2020
url https://hdl.handle.net/10356/142715
_version_ 1681058512258465792