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Unveiling Bias Compensation in Turbo-Based Algorithms for (Discrete) Compressed Sensing - MaRDI portal

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Unveiling Bias Compensation in Turbo-Based Algorithms for (Discrete) Compressed Sensing

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Publication:6283813

arXiv1703.00707MaRDI QIDQ6283813

Author name not available (Why is that?)

Publication date: 2 March 2017

Abstract: In Compressed Sensing, a real-valued sparse vector has to be recovered from an underdetermined system of linear equations. In many applications, however, the elements of the sparse vector are drawn from a finite set. Adapted algorithms incorporating this additional knowledge are required for the discrete-valued setup. In this paper, turbo-based algorithms for both cases are elucidated and analyzed from a communications engineering perspective, leading to a deeper understanding of the algorithm. In particular, we gain the intriguing insight that the calculation of extrinsic values is equal to the unbiasing of a biased estimate and present an improved algorithm.












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