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Improved Stochastic Gradient Matching Pursuit Algorithm Based on the Soft-Thresholds Selection
Joint Authors
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-09-24
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Information Technology and Computer Science
Abstract EN
The preliminary atom set exits redundant atoms in the stochastic gradient matching pursuit algorithm, which affects the accuracy of the signal reconstruction and increases the computational complexity.
To overcome the problem, an improved method is proposed.
Firstly, a limited soft-threshold selection strategy is used to select the new atoms from the preliminary atom set, to reduce the redundancy of the preliminary atom set.
Secondly, before finding the least squares solution of the residual, it is determined whether the number of columns of the measurement matrix is smaller than the number of rows.
If the condition is satisfied, the least squares solution is calculated; otherwise, the loop is exited.
Finally, if the length of the candidate atomic index set is less than the sparsity level, the current candidate atom index set is the support atom set.
If the condition is not satisfied, the support atom index set is determined by the least squares solution.
Simulation results indicate that the proposed method is better than other methods in terms of the reconstruction probability and shorter running time than the stochastic gradient matching pursuit algorithm.
American Psychological Association (APA)
Zhao, Liquan& Yunfeng, Hu. 2018. Improved Stochastic Gradient Matching Pursuit Algorithm Based on the Soft-Thresholds Selection. Journal of Electrical and Computer Engineering،Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1184560
Modern Language Association (MLA)
Zhao, Liquan& Yunfeng, Hu. Improved Stochastic Gradient Matching Pursuit Algorithm Based on the Soft-Thresholds Selection. Journal of Electrical and Computer Engineering No. 2018 (2018), pp.1-11.
https://search.emarefa.net/detail/BIM-1184560
American Medical Association (AMA)
Zhao, Liquan& Yunfeng, Hu. Improved Stochastic Gradient Matching Pursuit Algorithm Based on the Soft-Thresholds Selection. Journal of Electrical and Computer Engineering. 2018. Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1184560
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1184560