Publication:
Soft Homotopy through Moore-Penrose Inverse

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Issued Date

2022

Resource Type

Article

Language

eng

File Type

application/pdf

DOI

10.1109/CIVEMSA53371.2022.9853651

Rights Holder(s)

Scopus

Bibliographic Citation

Carbohydrate Polymers. Vol 297, No. (2022), p.-

Suggested Citation

Tausiesakul B. Soft Homotopy through Moore-Penrose Inverse. Carbohydrate Polymers. Vol 297, No. (2022), p.-. doi:10.1109/CIVEMSA53371.2022.9853651 Retrieved from: https://hdl.handle.net/20.500.14740/9982

Title

Soft Homotopy through Moore-Penrose Inverse

Author(s)

Tausiesakul B.

Abstract

The acquisition of a discrete-time signal is an important part of a compressive sensing problem. A fine algorithm that could bring better signal recovery performance is often called for. In this work, two homotopy algorithms that involve a soft thresholding decision are proposed using the Moore-Penrose inverse. The additional complexity required in the two proposed methods is relatively minimal, since the necessary matrix inverse (AA⊺)-1 and the matrix multiplication A⊺(AA⊺)-1 can be done before the iteration starts, where ·⊺ is the transpose. Numerical examples illustrate the improved error performance for different values of the shrinking parameter γ. It is found that the greater the shrinking parameter, the less the signal recovery error one could obtain from the two new approaches. © 2022 IEEE.

Subject(s)

Compressive sensing
 Homotopy algorithm
 Soft thresholding

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URI

https://hdl.handle.net/20.500.14740/9982

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Scopus: Year 2022

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