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General numerical methods
Search for sparse solutions of super-large systems with a tensor structure
D. A. Zheltkov, N. L. Zamarashkin, S. V. Morozov Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences, 119333, Moscow, Russia
Abstract:
The problem of finding a sparse solution to large systems of linear equations arises in many applications related to signal processing. Sometimes, the size of these systems is so large that the known methods are inefficient. Such systems can be solved only if there is additional structure inherent in them. In this paper, an efficient approach for finding sparse solutions to super-large systems of linear equations with a tensor structure of a certain type is proposed. The theoretical analysis and experimental results make it possible to judge the efficiency of the proposed method.
Key words:
least squares method, sparse solution, tensor structure of an operator.
Received: 30.12.2021 Revised: 06.06.2022 Accepted: 07.07.2022
Citation:
D. A. Zheltkov, N. L. Zamarashkin, S. V. Morozov, “Search for sparse solutions of super-large systems with a tensor structure”, Zh. Vychisl. Mat. Mat. Fiz., 62:11 (2022), 1804–1821; Comput. Math. Math. Phys., 62:11 (2022), 1782–1798
Linking options:
https://www.mathnet.ru/eng/zvmmf11467 https://www.mathnet.ru/eng/zvmmf/v62/i11/p1804
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