… , fashioned as an almost lossless analog compression problem. Specifically, [4] … ⌋ linear
measurements, provided that R>RB, where RB denotes the Minkowski dimension compression …

… Abstract—We establish the fundamental limits of lossless ana- log compression by considering
the recovery of arbitrary random vectors x ∈ Rm from the noiseless linear measurements …

… In this section, we analyze lossless compression with linear encoders, which are the basic
elements in compressed sensing. Capitalizing on the approach of Minkowski-dimension com…

… m = ⌊Rn⌋ phaseless measurements with compression rate R and derive a general achievability
… on the compression rate is the same as the one for almost lossless analog compression …

… Compressed sensing is a lossless coding strategy for analog … almost lossless analog
compression for analog memoryless … the compressor is not constrained to linear transformations …

… analog signal separation. Specifically, we consider the problem of recovering two analog
signals from a noiseless sum of linear … 18] in the context of almost lossless analog compression …

… In this setting, the theory of linear compression with efficient and stable recovery algorithms
has been developed. However, strong assumptions posed on the structure of the signal …

… Linear prediction is an effective decorrelation technique that can be completely reversible.
In the lossless coding literature, linear prediction is frequently referred to as differential pulse …

… compression scheme, most of the initial activity in the compression area focused on lossy
compression… One reason was that the" data" being considered for compression was analog-…

… In this paper, we study the lossless analog compression for … the polarization phenomenon to
analog domain. Building on this … partial Hadamard matrices for linear compression. Then the …