Title :
Stability Results for Random Sampling of Sparse Trigonometric Polynomials
Author_Institution :
NuHAG, Univ. of Vienna, Vienna
Abstract :
Recently, it has been observed that a sparse trigonometric polynomial, i.e., having only a small number of nonzero coefficients, can be reconstructed exactly from a small number of random samples using basis pursuit (BP) or orthogonal matching pursuit (OMP). In this paper, it is shown that recovery by a BP variant is stable under perturbation of the samples values by noise. A similar partial result for OMP is provided. For BP, in addition, the stability result is extended to (nonsparse) trigonometric polynomials that can be well approximated by sparse ones. The theoretical findings are illustrated by numerical experiments.
Keywords :
polynomial approximation; signal sampling; Fourier transform; basis pursuit; nonzero coefficients; orthogonal matching pursuit; random sampling stability; sparse trigonometric polynomials; stability under noise; Algorithm design and analysis; Compressed sensing; Discrete Fourier transforms; Fast Fourier transforms; Matching pursuit algorithms; Noise measurement; Polynomials; Reconstruction algorithms; Sampling methods; Stability; Basis pursuit (BP); compressed sensing; fast Fourier transform (FFT); nonequispaced fast Fourier transform (NFFT); orthogonal matching pursuit (OMP); random sampling; stability under noise; trigonometric polynomials;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2008.2006382