Physical Review E · 2004 · 81 citations · 7 references
EngineeringComputer ScienceMathematicsAlgorithmsDynamical SystemsInformation TheoryCoding TheoryData CompressionLossless Data CompressionLossy Data CompressionRate-distortion TheorySource CodingCompressed SensingCompressionData EncodingIll-posed Inverse ProblemsIll-posed ProblemsIterative CompressionRate-distortion FunctionRate-distortion Tradeoff
We study an ill-posed linear inverse problem, where a binary sequence will be reproduced using a sparse matrix. According to the previous study, this model can theoretically provide an optimal compression scheme for an arbitrary distortion level, though the encoding procedure remains an NP-complete problem. In this paper, we focus on the consistency condition for a dynamics model of Markov-type to derive an iterative algorithm, following the steps of Thouless-Anderson-Palmer approach. Numerical results show that the algorithm can empirically saturate the theoretical limit for the sparse construction of our codes, which is also very close to the rate-distortion function.
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A Mathematical Theory of Communication
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