Influences of preconditioning on the mutual coherence and the restricted isometry property of Gaussian/Bernoulli measurement matrices

Abstract

This article discusses the influence of preconditioning on the mutual coherence and the restricted isometry property of Gaussian or Bernoulli measurement matrices. The mutual coherence can be reduced by preconditioning, although it is fairly small due to the probability estimate of the event that it is less than any given number in (0, 1). This can be extended to a set that contains either of the two types of matrices with a high probability but a subset with Lebesgue measure zero. The numerical results illustrate the reduction in the mutual coherence of Gaussian or Bernoulli measurement matrices. However, the first property can be true after preconditioning for a large type of measurement matrices having the property of s-order restricted isometry and being full row rank. This leads to a better estimate of the condition number of the corresponding submatrices and a more accurate error estimate of the conjugate gradient methods for the least squares problems typically used in greedy-like recovery algorithms.