@inproceedings{772f4facb1894451962e659a66ac24e7,
title = "Maximum likelihood estimation under partial sparsity constraints",
abstract = "We consider the problem of estimating two deterministic vectors in a linear Gaussian model where one of the unknown vectors is subject to a sparsity constraint. We derive the maximum likelihood estimator for this problem and develop the Projected Orthogonal Matching Pursuit (POMP) algorithm for its practical implementation. The corresponding constrained Cram{\'e}r-Rao bound (CCRB) on the mean-square-error is developed under the sparsity constraint. We then show that estimation in linear dynamical systems with a sparse control can be formulated as a special case of this problem.",
keywords = "Sparsity, compressed sensing, constrained Cram{\'e}r-Rao, maximum likelihood estimation",
author = "Tirza Routtenberg and Eldar, {Yonina C.} and Lang Tong",
year = "2013",
month = oct,
day = "18",
doi = "10.1109/ICASSP.2013.6638902",
language = "English",
isbn = "9781479903566",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
pages = "6421--6425",
booktitle = "2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings",
note = "2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 ; Conference date: 26-05-2013 Through 31-05-2013",
}