The Rate-Distortion Function and Excess-Distortion Exponent of Sparse Regression Codes with Optimal Encoding
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Abstract
This paper studies the performance of sparse regression codes for lossy
compression with the squared-error distortion criterion. In a sparse regression
code, codewords are linear combinations of subsets of columns of a design
matrix. It is shown that with minimum-distance encoding, sparse regression
codes achieve the Shannon rate-distortion function for i.i.d. Gaussian sources
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1557-9654