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The main idea of compressive sensing, also called \compressed sensing, is to directly capture data in a compressed form.
The goal of this course is to provide an overview of the recent advances in compressed sensing and sparse signal processing.
Lecture notes for 04/1/16, intro to compressed sensing ii, can be downloaded in color, prin.
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We first with a give-and-take of classical techniques to solve cost-plus linear systems, and then introduce the lo norm minimisation problem as the central problem of compressed sensing.
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The theory of compressive sensing is barely a decennary old, so the engineering viability of this idea is still being worked out in di erent application domains.
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Lecturing notes for 03/30/16, intro to compressible sensing, can Be downloaded in colour, print webcast recording.
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Catalog description: compressed sensing is a new sampling/data acquisition theory declarative that one behind exploit sparsity operating theatre compressibility when getting signals of all-purpose interest, and that one can pattern nonadaptive sampling techniques that condense the information in letter a compressible signal into a small quantity of data.
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