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Concise Signal Models

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Collection by: Michael Wakin. E-mail the author

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Summary: This collection reviews fundamental concepts underlying the use of concise models for signal processing. Topics are presented from a geometric perspective and include low-dimensional linear, sparse, and manifold-based signal models, approximation, compression, dimensionality reduction, and Compressed Sensing.

This collection contains: Modules by: Michael Wakin.

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