Sparse Signal Reconstruction via Iterative Support Detection
نویسندگان
چکیده
منابع مشابه
Sparse Signal Reconstruction via Iterative Support Detection
We present a novel sparse signal reconstruction method “ISD”, aiming to achieve fast reconstruction and a reduced requirement on the number of measurements compared to the classical `1 minimization approach. ISD addresses failed reconstructions of `1 minimization due to insufficient measurements. It estimates a support set I from a current reconstruction and obtains a new reconstruction by solv...
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We present a new compressive sensing reconstruction method ISD, aiming to achieve fast reconstruction and a reduced requirement on the number of measurements compared to the classical l1 minimization approach. ISD addresses failed cases of l1–based construction due to insufficient measurements, in which the returned signals are not equal or even close to the true signals. ISD will learn from su...
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Compressed sensing (CS) [1, 2] demonstrates that sparse signals can be recovered from underdetermined linear measurements. The idea of iterative support detection (ISD, for short) method first proposed by Wang et. al [3] has demonstrated its superior performance for the reconstruction of the single channel sparse signals. In this paper, we extend ISD from sparsity to the more general structured...
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ژورنال
عنوان ژورنال: SIAM Journal on Imaging Sciences
سال: 2010
ISSN: 1936-4954
DOI: 10.1137/090772447