61 citations · 419 across the 59 of their papers we have counts for
6 papers · 1 filter
Alternating Strategies Are Good For Low-Rank Matrix Reconstruction
Kezhi Li, Martin Sundin, Cristian R. Rojas +2
This article focuses on the problem of reconstructing low-rank matrices from underdetermined measurements using alternating optimization strategies. We endeavour to combine an alte…
Estimation for the Linear Model with Uncertain Covariance Matrices
Dave Zachariah, Nafiseh Shariati, Mats Bengtsson +2
We derive a maximum a posteriori estimator for the linear observation model, where the signal and noise covariance matrices are both uncertain. The uncertainties are treated probab…
Line Spectrum Estimation with Probabilistic Priors
Dave Zachariah, Petter Wirfält, Magnus Jansson +1
For line spectrum estimation, we derive the maximum a posteriori probability estimator where prior knowledge of frequencies is modeled probabilistically. Since the spectrum is peri…
Dynamic Iterative Pursuit
Dave Zachariah, Saikat Chatterjee, Magnus Jansson
For compressive sensing of dynamic sparse signals, we develop an iterative pursuit algorithm. A dynamic sparse signal process is characterized by varying sparsity patterns over tim…
Alternating Least-Squares for Low-Rank Matrix Reconstruction
Dave Zachariah, Martin Sundin, Magnus Jansson +1
For reconstruction of low-rank matrices from undersampled measurements, we develop an iterative algorithm based on least-squares estimation. While the algorithm can be used for any…
Minimum Mean Square Error Estimation Under Gaussian Mixture Statistics
John T. Flam, Saikat Chatterjee, Kimmo Kansanen +1
This paper investigates the minimum mean square error (MMSE) estimation of x, given the observation y = Hx+n, when x and n are independent and Gaussian Mixture (GM) distributed. Th…