本书主要论述如下四个问题：1.Compressive Sensing and Structured Random Matrices; 2.Numerical Methods for Sparse Recovery; 3.Sparse Recovery in Inverse Problems; 4.An Introduction to Total Variation for Image Analysis.
MATLAB implementation of compressive sensing example as described in R. % Baraniuk, Compressive Sensing, IEEE Signal Processing Magazine, [118], % July 2007.
Compressive sensing is a topic that has recently gained much attention in the applied mathematics and signal processing communities. It has been applied in various areas, such as imaging, radar, speech recognition, and data acquisition. In communica
碳至钛表面拉-压应力转变，孙长庆，Yongqing Fu，The residual stresses of the Ti/TiC/Diamond interfaces have been characterized at different stages of diamond growth using Raman spectroscopy and X-ray diffraction. It is found tha
