5,576 research outputs found
Coherence-Based Performance Guarantees of Orthogonal Matching Pursuit
In this paper, we present coherence-based performance guarantees of
Orthogonal Matching Pursuit (OMP) for both support recovery and signal
reconstruction of sparse signals when the measurements are corrupted by noise.
In particular, two variants of OMP either with known sparsity level or with a
stopping rule are analyzed. It is shown that if the measurement matrix
satisfies the strong coherence property, then with
, OMP will recover a -sparse signal with high
probability. In particular, the performance guarantees obtained here separate
the properties required of the measurement matrix from the properties required
of the signal, which depends critically on the minimum signal to noise ratio
rather than the power profiles of the signal. We also provide performance
guarantees for partial support recovery. Comparisons are given with other
performance guarantees for OMP using worst-case analysis and the sorted one
step thresholding algorithm.Comment: appeared at 2012 Allerton conferenc
Orthogonal Matching Pursuit: A Brownian Motion Analysis
A well-known analysis of Tropp and Gilbert shows that orthogonal matching
pursuit (OMP) can recover a k-sparse n-dimensional real vector from 4 k log(n)
noise-free linear measurements obtained through a random Gaussian measurement
matrix with a probability that approaches one as n approaches infinity. This
work strengthens this result by showing that a lower number of measurements, 2
k log(n - k), is in fact sufficient for asymptotic recovery. More generally,
when the sparsity level satisfies kmin <= k <= kmax but is unknown, 2 kmax
log(n - kmin) measurements is sufficient. Furthermore, this number of
measurements is also sufficient for detection of the sparsity pattern (support)
of the vector with measurement errors provided the signal-to-noise ratio (SNR)
scales to infinity. The scaling 2 k log(n - k) exactly matches the number of
measurements required by the more complex lasso method for signal recovery with
a similar SNR scaling.Comment: 11 pages, 2 figure
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