Sparse Regression Codes
نویسنده
چکیده
Developing computationally-efficient codes that approach the Shannon-theoretic limits for communication and compression has long been one of the major goals of information and coding theory. There have been significant advances towards this goal in the last couple of decades, with the emergence of turbo and sparse-graph codes in the ‘90s [1, 2], and more recently polar codes and spatially-coupled LDPC codes [3–5]. These codes are all primarily for discrete-alphabet sources and channels.
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تاریخ انتشار 2016