Novel techniques for sparse representation problems

Sparse representations have been used in solving many problems in computer science. Two issues that need to be addressed in formulating such a representation are: the problem design; and the optimization technique. Many optimization problems contain one/multiple non-smooth terms in the objective f...

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Main Author: Chai, Woon Huei
Other Authors: Quek Hiok Chai
Format: Thesis-Doctor of Philosophy
Language:English
Published: Nanyang Technological University 2021
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Online Access:https://hdl.handle.net/10356/146392
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1463922023-03-05T16:38:02Z Novel techniques for sparse representation problems Chai, Woon Huei Quek Hiok Chai Interdisciplinary Graduate School (IGS) Energy Research Institute @ NTU (ERI@N) ASHCQUEK@ntu.edu.sg Engineering::Computer science and engineering Science::Mathematics Sparse representations have been used in solving many problems in computer science. Two issues that need to be addressed in formulating such a representation are: the problem design; and the optimization technique. Many optimization problems contain one/multiple non-smooth terms in the objective function. Besides, the feasibility of an optimization problem depends on the availability of adequate computational resources. In this thesis, a new parallelizable optimization technique that uses more information and has better convergence than state-of-the-art counterparts is presented. Theoretical derivation of the bound of the recovery probability of using sparse representation based on a L_1-minimization is also shown. A clustering-based technique for dictionary and signal dimension reduction to replace the traditional naïve downsampling technique is introduced to address computational resource constraints. Finally, an anomaly detection and localization technique using a sparse representation problem and used in a case study for an important and challenging field; namely automated visual inspection (AVI) is presented. The experimental results are encouraging. Doctor of Philosophy 2021-02-16T01:29:59Z 2021-02-16T01:29:59Z 2021 Thesis-Doctor of Philosophy Chai, W. H. (2021). Novel techniques for sparse representation problems. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/146392 10.32657/10356/146392 en This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering
Science::Mathematics
spellingShingle Engineering::Computer science and engineering
Science::Mathematics
Chai, Woon Huei
Novel techniques for sparse representation problems
description Sparse representations have been used in solving many problems in computer science. Two issues that need to be addressed in formulating such a representation are: the problem design; and the optimization technique. Many optimization problems contain one/multiple non-smooth terms in the objective function. Besides, the feasibility of an optimization problem depends on the availability of adequate computational resources. In this thesis, a new parallelizable optimization technique that uses more information and has better convergence than state-of-the-art counterparts is presented. Theoretical derivation of the bound of the recovery probability of using sparse representation based on a L_1-minimization is also shown. A clustering-based technique for dictionary and signal dimension reduction to replace the traditional naïve downsampling technique is introduced to address computational resource constraints. Finally, an anomaly detection and localization technique using a sparse representation problem and used in a case study for an important and challenging field; namely automated visual inspection (AVI) is presented. The experimental results are encouraging.
author2 Quek Hiok Chai
author_facet Quek Hiok Chai
Chai, Woon Huei
format Thesis-Doctor of Philosophy
author Chai, Woon Huei
author_sort Chai, Woon Huei
title Novel techniques for sparse representation problems
title_short Novel techniques for sparse representation problems
title_full Novel techniques for sparse representation problems
title_fullStr Novel techniques for sparse representation problems
title_full_unstemmed Novel techniques for sparse representation problems
title_sort novel techniques for sparse representation problems
publisher Nanyang Technological University
publishDate 2021
url https://hdl.handle.net/10356/146392
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