The literature on compressed sensing has focused almost entirely on settings where the signal is noiseless and the measurements are contaminated by noise. In practice, however, th...
Compressive sensing (CS) exploits the sparsity present in many common signals to reduce the number of measurements needed for digital acquisition. With this reduction would come, ...
Mark A. Davenport, Jason N. Laska, John R. Treichl...
Abstract--This paper describes performance bounds for compressed sensing (CS) where the underlying sparse or compressible (sparsely approximable) signal is a vector of nonnegative ...
Maxim Raginsky, Rebecca Willett, Zachary T. Harman...
In fluorescence microscopy the noise level and the photobleaching are cross-dependent problems since reducing exposure time to reduce photobleaching degrades image quality while ...
Marcio de Moraes Marim, Elsa D. Angelini, Jean-Chr...
This short note studies a variation of the Compressed Sensing paradigm introduced recently by Vaswani et al., i.e. the recovery of sparse signals from a certain number of linear m...