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access icon free Expectation maximisation-based approach to recovering multiple sparse signals with common sparsity pattern

The problem of simultaneously recovering multiple sparse signals bearing a common sparsity pattern is addressed. Specifically, a common Gaussian prior to all the sparse signals under consideration is assigned. This can make that the signals share the same sparsity pattern. Then, an expectation maximisation (EM)-based approach to learn the priori parameters from measurements, thereby leading to the recovery of sparse signals is adopted. Simulations verify that the proposed EM approach outperforms the state-of-the-art counterparts.

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      • 2. Cheng, X., Wang, M., Li, S.: ‘Compressive sensing-based beamforming for millimeter-wave OFDM systems’, Trans. Commun., 2017, 65, pp. 371386.
http://iet.metastore.ingenta.com/content/journals/10.1049/el.2017.1913
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content/journals/10.1049/el.2017.1913
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