Publication:
Iterative Hard Thresholding Using Least Squares Initialization

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Issued Date

2022

Resource Type

Article

Language

eng

File Type

application/pdf

DOI

10.1109/CSNT54456.2022.9787592

Rights Holder(s)

Scopus

Bibliographic Citation

Journal of Chemical Education. Vol , No. (2022), p.-

Suggested Citation

Tausiesakul B. Iterative Hard Thresholding Using Least Squares Initialization. Journal of Chemical Education. Vol , No. (2022), p.-. doi:10.1109/CSNT54456.2022.9787592 Retrieved from: https://hdl.handle.net/20.500.14740/9472

Title

Iterative Hard Thresholding Using Least Squares Initialization

Author(s)

Tausiesakul B.

Abstract

An improvement of the typical iterative hard thresholding (IHT) algorithm is presented by means of least squares initialization. Unlike the initialization that assigns all zeros to the initial estimate, the linearized least squares estimate is instead adopted herein. Numerical examples are conducted under a sparse signal recovery problem. Performance of the proposed approach in terms of root-mean-square relative error (RMSRE), computational time, and memory consumption is compared to the typical IHT algorithm. It is shown in numerical example that a good initialization can deliver lower RMSRE, less computational time, and less memory requirement. © 2022 IEEE.

Subject(s)

Compressive sensing
 Iterative hard thresholding
 Linear least squares

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URI

https://hdl.handle.net/20.500.14740/9472

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Scopus: Year 2022

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