Thouless-Anderson-Palmer Approach for Lossy Compression
classification
❄️ cond-mat.dis-nn
keywords
algorithmcompressionmodelproblemthouless-anderson-palmeraccordingapproacharbitrary
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We study an ill-posed linear inverse problem, where a binary sequence will be reproduced using a sparce 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's. Numerical results show that the algorithm can empirically saturate the theoretical limit for the sparse construction of our codes, which also is very close to the rate-distortion function.
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