In this paper, we adopt a parametric joint recovery-estimation method based on model selection in spectral compressive sensing. Numerical experiments show that ...

Nov 27, 2013 · In this paper, we adopt a parametric joint recovery-estimation method based on model selection in spectral compressive sensing. Numerical ...

Numerical experiments show that this parametric joint recovery-estimation method based on model selection in spectral compressive sensing outperforms most ...

In this paper, we adopt a parametric joint recovery-estimation method based on model selection in spectral compressive sensing. Numerical experiments show that ...

Compressive sensing (CS) is a new approach to simultaneous sensing and compression of sparse and compressible signals based on randomized dimensionality ...

This is done by using a sequential forward floating selection method [28,41] that aims to achieve a highly incoherent set of measurements. 4.2. Staring Mode.

We demonstrate numerally compressive spectral sensing with approximately ten times fewer measurements than with an equivalent conventional spectrometer.

The effectiveness of the method is demonstrated on homogenization examples, where its complexity is dependent only on the sparsity of the problem and constant ...

Mar 5, 2019 · To reduce the size of spectral data, compressive sensing imaging systems are developed to sample fewer measurements than the Nyquist-rate ...