A novel underdetermined source recovery algorithm based on k-sparse component analysis

Eqlimi, E., Makkiabadi, B., Samadzadehaghdam, N., Khajehpour, H., Mohagheghian, F. and Sanei, S. ORCID: 0000-0002-3437-2801, 2018. A novel underdetermined source recovery algorithm based on k-sparse component analysis. Circuits, Systems, and Signal Processing. ISSN 0278-081X

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Abstract

Sparse component analysis (SCA) is a popular method for addressing underdetermined blind source separation in array signal processing applications. We are motivated by problems that arise in the applications where the sources are densely sparse (i.e. the number of active sources is high and very close to the number of sensors). The separation performance of current underdetermined source recovery (USR) solutions, including the relaxation and greedy families, reduces with decreasing the mixing system dimension and increasing the sparsity level (k). In this paper, we present a k-SCA-based algorithm that is suitable for USR in low-dimensional mixing systems. Assuming the sources is at most (m−1) sparse where m is the number of mixtures; the proposed method is capable of recovering the sources from the mixtures given the mixing matrix using a subspace detection framework. Simulation results show that the proposed algorithm achieves better separation performance in k-SCA conditions compared to state-of-the-art USR algorithms such as basis pursuit, minimizing norm-L1, smoothed L0, focal underdetermined system solver and orthogonal matching pursuit.

Item Type: Journal article
Publication Title: Circuits, Systems, and Signal Processing
Creators: Eqlimi, E., Makkiabadi, B., Samadzadehaghdam, N., Khajehpour, H., Mohagheghian, F. and Sanei, S.
Publisher: Birkhaeuser Science
Date: 3 August 2018
ISSN: 0278-081X
Identifiers:
NumberType
10.1007/s00034-018-0910-9DOI
910Publisher Item Identifier
Divisions: Schools > School of Science and Technology
Depositing User: Jonathan Gallacher
Date Added: 09 Aug 2018 10:48
Last Modified: 03 Aug 2019 03:00
URI: http://irep.ntu.ac.uk/id/eprint/34300

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