Chevet type inequality and norms of submatrices

We prove a Chevet type inequality which gives an upper bound for the norm of an isotropic log-concave unconditional random matrix in terms of expectation of the supremum of “symmetric exponential” processes compared to the Gaussian ones in the Chevet inequality. This is used to give sharp upper estimate for a quantity Γk,m that controls uniformly the Euclidean operator norm of the sub-matrices with k rows and m columns of an isotropic log-concave unconditional random matrix. We apply these estimates to give a sharp bound for the Restricted Isometry Constant of a random matrix with independent log-concave unconditional rows. We also show that our Chevet type inequality does not extend to general isotropic log-concave random matrices. AMS 2010 Classification: Primary 52A23, 46B06, 46B09, 60B20; Secondary 15B52, 60E15, 94B75.