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Near Optimal Signal Recovery From Random Projections:Universal Encoding Strategies?
Random matrices singular values of random matrices signal recovery random projections concentration of measure sparsity trigonometric expansions uncertainty principle convex optimization duality in optimization linear programming
2015/6/17
Suppose we are given a vector f in a class F ⊂ RN, e.g. a class of digital signals or digital images. How many linear measurements do we need to make about f to be able to recover f to within pr...
Can we recover a signal f ∈ RN from a small number of linear measurements? A series of recent papers developed a collection of results showing that it is surprisingly possible to reconstruct certain t...