Concentration of measure for block diagonal measurement matrices

Concentration of measure inequalities are at the heart of much theoretical analysis of randomized compressive operators. Though commonly studied for dense matrices, in this paper we derive a concentration of measure bound for block diagonal matrices where the nonzero entries along the main diagonal blocks are i.i.d. subgaussian random variables. Our main result states that the concentration exponent, in the best case, scales as that for a fully dense matrix. We also identify the role that the energy distribution of the signal plays in distinguishing the best case from the worst. We illustrate these phenomena with a series of experiments.

• Type: Conference
• Year: 2010
• Where: ICASSP
• Authors: Michael B. Wakin, Jae Young Park, Han Lun Yap, Christopher J. Rozell
• Keywords: Block Diagonal Matrices, ICASSP 2010, Main Diagonal Blocks, Signal Processing, Subgaussian Random Variables