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Title

Compare Performance of Recovery Algorithms MP, OMP, L1-Norm in Compressive Sensing for Different Measurement and Sparse Spaces

Year: 1396
COI: JR_SPRE-1-3_003
Language: EnglishView: 255
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Authors

Bahareh Davoodi - Electrical Engineering Department South Tehran Branch, Islamic Azad University Tehran, Iran
Sedigheh Ghofrani - Electrical Engineering Department South Tehran Branch, Islamic Azad University Tehran, Iran

Abstract:

In this paper, at first, compressive sensing theory involves introducing measurement matrices to dedicate the signal dimension and so sensing cost reduction, and sparse domain to examine the conditions for the possibility of signal recovering, are explained. In addition, three well known recovery algorithms called Matching Pursuit (MP), Orthogonal Matching Pursuit (OMP), and L1-Norm are briefly introduced. Then, the performance of three mentioned recovery algorithms are compared with respect to the mean square error (MSE) and the result images quality. For this purpose, Gaussian and Bernoulli as the measurement matrices are used, where Haar and Fourier as sparse domains are applied.

Keywords:

Paper COI Code

This Paper COI Code is JR_SPRE-1-3_003. Also You can use the following address to link to this article. This link is permanent and is used as an article registration confirmation in the Civilica reference:

https://civilica.com/doc/897081/

How to Cite to This Paper:

If you want to refer to this Paper in your research work, you can simply use the following phrase in the resources section:
Davoodi, Bahareh and Ghofrani, Sedigheh,1396,Compare Performance of Recovery Algorithms MP, OMP, L1-Norm in Compressive Sensing for Different Measurement and Sparse Spaces,https://civilica.com/doc/897081

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Scientometrics

The specifications of the publisher center of this Paper are as follows:
Type of center: Azad University
Paper count: 12,182
In the scientometrics section of CIVILICA, you can see the scientific ranking of the Iranian academic and research centers based on the statistics of indexed articles.

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COI stands for "CIVILICA Object Identifier". COI is the unique code assigned to articles of Iranian conferences and journals when indexing on the CIVILICA citation database.

The COI is the national code of documents indexed in CIVILICA and is a unique and permanent code. it can always be cited and tracked and assumed as registration confirmation ID.

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