Compressibility of Infinite Sequences and Its Interplay with Compressed Sensing Recovery

Provided by: Universidad de Castilla y la Mancha
Topic: Networking
Format: PDF
This paper elaborates connections between notions of compressibility of infinite sequences, recently addressed by Amini et al., and the performance of the Compressed Sensing (CS) type of recovery algorithms from linear measurements in the under-sample scenario. In particular, in the asymptotic regime when the signal dimension goes to infinity, the authors established a new set of compressibility definitions over infinite sequences that guarantee arbitrary good performance in an l1-noise to signal ratio (l1-NSR) sense with an arbitrary close to zero number of measurements per signal dimension.

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