Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
California Institute of Technology · University of California, Los Angeles
Abstract
This paper considers the model problem of reconstructing an object from incomplete frequency samples. Consider a discrete-time signal f/spl isin/C/sup N/ and a randomly chosen set of frequencies /spl Omega/. Is it possible to reconstruct f from the partial knowledge of its Fourier coefficients on the set /spl Omega/? A typical result of this paper is as follows. Suppose that f is a superposition of |T| spikes f(t)=/spl sigma//sub /spl tau//spl isin/T/f(/spl tau/)/spl delta/(t-/spl tau/) obeying |T|/spl les/C/sub M//spl middot/(log N)/sup -1/ /spl middot/ |/spl Omega/| for some constant C/sub M/>0. We do not know the locations of the spikes nor their amplitudes. Then with probability at least 1-O(N/sup -M/), f…
Citation impact
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- 438.57
- Percentile
- 100%
- References
- 36
Authors
3Topics & keywords
- Omega
- Combinatorics
- Mathematics
- Signal reconstruction
- Superposition principle
- Convex optimization
- Discrete mathematics
- Regular polygon