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We present a cooperative compressed sensing scheme for wide-band spectrum detection in cognitive radio where analog-to-information converter are applied to map a continuous-time signal to a discrete sequence of measurements. The measurements are collected from each second user to a fusion center where a novel cooperative compressed sensing recovery algorithm named SCSMP is utilized to reconstruct...
In this paper, a matrix form of Sym wavelet synthesis is deduced, keeping the length of the coefficient no more than the length of original speech signals, and then we propose an Adaptive Multiscale Compressed Sensing (AMCS) method, which design the sensing matrix and the num of level of wavelet decomposition adaptively, according to the sparsity of each level wavelet coefficients of the speech signals...
Compressed sensing (CS) is an emerging signal acquisition theory that provides a universal approach for characterizing signals which are sparse or compressible on some basis at sub-Nyquist sampling rate. This paper focuses on the realization of CS on natural speech signals. We construct an over-complete data-driven dictionary as the sparse basis specialized for speech signals. Based on this, CS sampling...
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