Error correction via smoothed L0-norm recovery

Saman Ashkiani (1) , Massoud Babaie-Zadeh (1) , Christian Jutten (2)

1 EE department of SUT [Tehran] - Department of Electrical Engineering [Tehran]
2 GIPSA-VIBS - GIPSA - Vision and Brain Signal Processing

Channel coding has been considered as a classical approach to overcome corruptions occurring in some elements of input signal which may lead to loss of some information. Proper redundancies are added to the input signal to improve the capability of detecting or even correcting the corrupted signal. A similar scenario may happen dealing with real-field numbers rather than finite-fields. This paper considers a way to reconstruct an exact version of a corrupted signal by using an encoded signal with proper number of redundancies. The proposed algorithm uses Graduated Non-Convexity method beside using a smoothed function instead of 0-norm to correct all the corrupted elements. Simulations show that our proposed algorithm substantially improves the probability of exact recovery in comparison to previous algorithms.

Mots clés: Compressed Sensing; Real-field coding; Sparse Signal Processing

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Saman Ashkiani, Massoud Babaie-Zadeh, Christian Jutten. Error correction via smoothed L0-norm recovery. SSP 2011 - 2011 IEEE Workshop on Statistical Signal Processing, Jun 2011, Nice, France. pp.289-292. ⟨hal-00605696⟩