DEEP NEURAL NETWORK-BASED APPROACH FOR COMPUTING SINGULAR VALUES OF MATRICES
Matrix factorization techniques, such as Singular Value Decomposition (SVD), Eigenvalue Decomposition (EVD), and QR decomposition, have long been pivotal in computational mathematics, particularly for applications in signal processing, machine learning, and data analysis. With the growing size and...
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University of Zakho
2025-01-01
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| Series: | Science Journal of University of Zakho |
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| Online Access: | http://sjuoz.uoz.edu.krd/index.php/sjuoz/article/view/1345 |
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| author | Diyari A. Hassan |
| author_facet | Diyari A. Hassan |
| author_sort | Diyari A. Hassan |
| collection | DOAJ |
| description |
Matrix factorization techniques, such as Singular Value Decomposition (SVD), Eigenvalue Decomposition (EVD), and QR decomposition, have long been pivotal in computational mathematics, particularly for applications in signal processing, machine learning, and data analysis. With the growing size and complexity of data, traditional methods of matrix factorization face challenges in efficiency and scalability. This paper investigates the implementation of Convolutional Neural Networks (CNNs) for computing the singular values of both real and complex matrices. By leveraging the hierarchical feature extraction capabilities of CNNs, this approach aims to enhance the accuracy, efficiency, and scalability of SVD calculations. The proposed CNN-based SVD method is evaluated against the conventional SVD algorithm, demonstrating superior performance in terms of computational time and accuracy.
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| format | Article |
| id | doaj-art-c8237fe674bd4d75b5fc83b5d7a02ec5 |
| institution | Kabale University |
| issn | 2663-628X 2663-6298 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | University of Zakho |
| record_format | Article |
| series | Science Journal of University of Zakho |
| spelling | doaj-art-c8237fe674bd4d75b5fc83b5d7a02ec52025-01-07T02:26:12ZengUniversity of ZakhoScience Journal of University of Zakho2663-628X2663-62982025-01-0113110.25271/sjuoz.2025.13.1.1345DEEP NEURAL NETWORK-BASED APPROACH FOR COMPUTING SINGULAR VALUES OF MATRICESDiyari A. Hassan0Faculty of Engineering & Computer Science, Qaiwan International University Sulaymaniyah, Kurdistan Region-Iraq Matrix factorization techniques, such as Singular Value Decomposition (SVD), Eigenvalue Decomposition (EVD), and QR decomposition, have long been pivotal in computational mathematics, particularly for applications in signal processing, machine learning, and data analysis. With the growing size and complexity of data, traditional methods of matrix factorization face challenges in efficiency and scalability. This paper investigates the implementation of Convolutional Neural Networks (CNNs) for computing the singular values of both real and complex matrices. By leveraging the hierarchical feature extraction capabilities of CNNs, this approach aims to enhance the accuracy, efficiency, and scalability of SVD calculations. The proposed CNN-based SVD method is evaluated against the conventional SVD algorithm, demonstrating superior performance in terms of computational time and accuracy. http://sjuoz.uoz.edu.krd/index.php/sjuoz/article/view/1345Singular Value DecompositionMatrix FactorizationConvolutional Neural NetworksComputational Compelxity |
| spellingShingle | Diyari A. Hassan DEEP NEURAL NETWORK-BASED APPROACH FOR COMPUTING SINGULAR VALUES OF MATRICES Science Journal of University of Zakho Singular Value Decomposition Matrix Factorization Convolutional Neural Networks Computational Compelxity |
| title | DEEP NEURAL NETWORK-BASED APPROACH FOR COMPUTING SINGULAR VALUES OF MATRICES |
| title_full | DEEP NEURAL NETWORK-BASED APPROACH FOR COMPUTING SINGULAR VALUES OF MATRICES |
| title_fullStr | DEEP NEURAL NETWORK-BASED APPROACH FOR COMPUTING SINGULAR VALUES OF MATRICES |
| title_full_unstemmed | DEEP NEURAL NETWORK-BASED APPROACH FOR COMPUTING SINGULAR VALUES OF MATRICES |
| title_short | DEEP NEURAL NETWORK-BASED APPROACH FOR COMPUTING SINGULAR VALUES OF MATRICES |
| title_sort | deep neural network based approach for computing singular values of matrices |
| topic | Singular Value Decomposition Matrix Factorization Convolutional Neural Networks Computational Compelxity |
| url | http://sjuoz.uoz.edu.krd/index.php/sjuoz/article/view/1345 |
| work_keys_str_mv | AT diyariahassan deepneuralnetworkbasedapproachforcomputingsingularvaluesofmatrices |