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Chaotic cellular automaton for generating measurement matrix used in CS coding

Chaotic cellular automaton for generating measurement matrix used in CS coding

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Exact compressed sensing (CS) recovery theoretically depends on a large number of random measurements. In this study, the authors present a novel CS measurement technique based on the cellular automata chaos (CAC) model. The proposed method selects original signal thresholding (OST) as its initial seed to realise CS signal coding. The benefits of CS coding with CAC-OST are that: (i) the signal compression ratio of this coding method can be far below the signal sparsity level and (ii) the signal can be recovered perfectly, even with slow CS measurements. This study reports some experiments that demonstrate the excellent performance of CAC-OST in CS coding.

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