Compressed Sensing with coherent tight frames via $l_q$-minimization for $0<q\leq1$

Details Compressed Sensing with coherent tight frames via $l_q$-minimization for $0<q\leq1$ Compressed Sensing with coherent tight frames via $l_q$-minimization for $0<q\leq1$

2011-05-17

arxiv.org/abs/1105.3299v2

Mathematics

Numerical Analysis

Scientific paper

Our aim of this article is to reconstruct a signal from undersampled data in the situation that the signal is sparse in terms of a tight frame. We present a condition, which is independent of the coherence of the tight frame, to guarantee accurate recovery of signals which are sparse in the tight frame, from undersampled data with minimal $l_1$-norm of transform coefficients. This improves the result in [1]. Also, the $l_q$-minimization $(0

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