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Conference Papers Year : 2012

Underdetermined Source Separation of Finite Alphabet Signals Via L1 Minimization

Abstract

This paper addresses the underdetermined source separation problem of finite alphabet signals. We present a new framework for recovering finite alphabet signals. We formulate this problem as a recovery of sparse signals from highly incomplete measurements. It is known that sparse solutions can be obtained by L_1 minimization, through convex optimization. This relaxation procedure in our problem fails in recovering sparse solutions. However, this does not impact the reconstruction of the finite alphabet signals. Simulation results are presented to show that this approach provides good recovery properties and good images separation performance.
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Dates and versions

hal-00725038 , version 1 (23-08-2012)
hal-00725038 , version 2 (20-08-2015)

Identifiers

  • HAL Id : hal-00725038 , version 2

Cite

Si Mohamed Aziz Sbai, Abdeldjalil Aissa El Bey, Dominique Pastor. Underdetermined Source Separation of Finite Alphabet Signals Via L1 Minimization. ISSPA 2012: 11th IEEE International Conference on Information Sciences, Signal Processing and their Applications, Jul 2012, Montreal, Quebec, Canada. pp.625 - 628. ⟨hal-00725038v2⟩
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