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Performance measure for sparse recovery algorithms in compressed sensing perspective

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Abstract

The sparse signal recovery is of great interest in compressed sensed data recovery. Many sparse recovery algorithms were developed in the last decade. However, selection of an appropriate recovery algorithm is an important matter of concern in many applications. The recovery algorithms are generally compared in terms of computational complexity, computational time, recovery probability and recovery precision. Typically, absolute Mean Squared Error (MSE) and relative MSE are used to compare the recovery precision of various sparse recovery algorithms. However, these two metric alone may not qualify to assess all algorithms. This paper presents an algorithm evaluation strategy by ranking the algorithms concerning an observable similarity between the original and reconstructed signal. We aim to propose a recovery similarity measure and an empirically defined factor to compare the performance measure of sparse recovery algorithms.

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Acknowledgements

The authors would like to acknowledge the authors of different algorithms for their support in the implementation of the algorithms using MATLAB. The research on sparse recovery algorithms has been made possible using the facility available at Indian Institute of Space Science and Technology, Vikram Sarabhai Space Centre and Indian Space Research Organisation.

Funding

The research on sparse recovery algorithms is supported by Indian Space Research Organisation, Government of India. Conflict of Interest: None of the authors of this manuscript has conflict of interest with any of the matter or materials discussed in the document. Data Availability: The data and simulation code used in the illustration are available up on request. Code Availability: The algorithm is developed used MATLAB software and is available on request.

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Authors and Affiliations

  1. Vikram Sarabhai Space Centre, Indian Space Research Organisation, Thiruvananthapuram, India

    V. Vivekanand

  2. Department of Space, Indian Institute of Space Science and Technology, Thiruvananthapuram, India

    Deepak Mishra

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  1. V. Vivekanand
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  2. Deepak Mishra
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Correspondence to V. Vivekanand.

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Vivekanand, V., Mishra, D. Performance measure for sparse recovery algorithms in compressed sensing perspective. Int J Data Sci Anal 15, 391–406 (2023). https://doi.org/10.1007/s41060-022-00357-6

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