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Sparse Regression Codes - Venkataramanan, Ramji, and Tatikonda, Sekhar, and Barron, Andrew
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Developing increasingly computationally-efficient codes for communication and compression has been the major goal of information and coding theory. There have been significant advances towards this goal in the last couple of decades with the emergence of turbo codes, sparse-graph codes, and polar codes. The world has seen faster network speeds and greater storage due to many of these developments. A new class of codes, Sparse Regression Codes (SPARCs), are a promising class of codes for achieving the Shannon limits of a ...

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Sparse Regression Codes 2019, now publishers Inc, Hanover

ISBN-13: 9781680835809

Paperback