Optimization research of Gauss matrices in compressive sensing.

This paper compared and analyzed statistical parameters of partial Hadamard matrices and Gauss matrices in order to optimize Gauss matrices. It determined the main influencing factors that led to partial Hadamard matrices' excellent behavior. Moreover, this paper proposed the optimization algorithm of Gauss matrices. It verified the validation and generality of optimization algorithm by Gauss matrices of different size, and determined optimal matrices' applicability to different sparse signal reconstruction algorithms. At last, it conducted preliminary theory experiment analysis of optimal matrices' performance. Optimal matrices were as much as partial Hadamard matrices more in the signal recovery ability. The research results provide a new idea and method for the analysis, design and optimization of measurement matrices. [ABSTRACT FROM AUTHOR]