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We consider the recovery of polynomials that are sparse with respect to the basis of Legendre polynomials from a small number of random sampling points. We show that a Legendre s-sparse polynomial of maximal degree N can be recovered from m ? s log4(N) random samples that are chosen independently according to the Chebyshev probability measure ??R??1(1 - x2)-1/2dx on [-1; 1]. As an efficient recovery...
Sparse representations have emerged as a powerful tool in signal and information processing, culminated by the success of new acquisition and processing techniques such as Compressed Sensing (CS). Fusion frames are very rich new signal representation methods that use collections of subspaces instead of vectors to represent signals. These exciting fields have been recently combined to introduce a new...
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