Compressive sensing (CS) is an emerging field that, under appropriate conditions, can significantly reduce the number of measurements required for a given signal. In many applicat...
Yuting Qi, Dehong Liu, David B. Dunson, Lawrence C...
Compressed sensing is a new area of signal processing. Its goal is to minimize the number of samples that need to be taken from a signal for faithful reconstruction. The performan...
This paper introduces a new problem for which machine-learning tools may make an impact. The problem considered is termed "compressive sensing", in which a real signal o...
Compressive Sensing (CS) uses a relatively small number of non-traditional samples in the form of randomized projections to reconstruct sparse or compressible signals. The Hough t...
Ali Cafer Gurbuz, James H. McClellan, Justin K. Ro...
Compressive sensing (CS) is an emerging approach for acquisition of signals having a sparse or compressible representation in some basis. While CS literature has mostly focused on...