It is known that use of a random measurement (sensing) matrix usually results in good recovery performance via orthogonal matching pursuit. This paper provides the probability of ensuring the recovery of sparse signals using orthogonal matching pursuit for the case where all entries of the measurement matrix are independently selected from a Gaussian distribution. The analysis relies on the mutual-coherence property of the sensing matrix.
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