Soft Thresholding Using Moore-Penrose Inverse
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Issued Date
2023-01-01
Resource Type
ISSN
00189456
eISSN
15579662
Scopus ID
2-s2.0-85163448421
Journal Title
IEEE Transactions on Instrumentation and Measurement
Rights Holder(s)
SCOPUS
Bibliographic Citation
IEEE Transactions on Instrumentation and Measurement (2023)
Suggested Citation
Tausiesakul B., Asavaskulkiet K. Soft Thresholding Using Moore-Penrose Inverse. IEEE Transactions on Instrumentation and Measurement (2023). doi:10.1109/TIM.2023.3289506 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/87938
Title
Soft Thresholding Using Moore-Penrose Inverse
Author(s)
Author's Affiliation
Other Contributor(s)
Abstract
The acquisition of a discrete-time signal is an important part of a compressive sensing problem. A high-accuracyalgorithm that could bring better signal recovery performance is often called for. In this work, two thresholding algorithms that involve a soft thresholding decision are proposed using the Moore-Penrose inverse. Numerical examples are conducted and illustrate that in the optimal case, both proposed methods consume the computational time in the same level as the conventional soft homotopy algorithm (SHA). Under no knowledge of the optimal regularization parameter, both methods will perform better than the conventional SHA with less amount of required time for the computation. Taking the non-sparse electroencephalogram signal from a real measurement into account, all soft thresholding algorithms provide nearly the same error performance for several compression ratios, while the proposed methods consume less computational time than the conventional SHA.