7 Fundamental thresholds in compressed sensing : a high - dimensional geometry approach
نویسندگان
چکیده
In this chapter, we introduce a unjfied rugh-dimensional geometric framework for analyzing the phase transition phenomenon of (1 minimization in compressive sensing. This framework connects srudying the phase transitions of ( 1 minimization with computing the Grassmann angles in high-dimensional convex geometry. We demonstrate the broad applications of this Grassmann angle framework by giving sharp phase transitions for £1 minimization recovery robustness. weighted {1 minimization algorithms. and iterative reweighted £1 minimjzation algorithms.
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