@inproceedings{b0669aa45d0041f4acf67c007b293579,
title = "Adaptive distributed compressed estimation based on recursive least squares with sensing matrix design",
abstract = "In this paper, a distributed compressed estimation (DCE) scheme is presented based on a distributed recursive-least squares algorithm for sparse signals and systems along with a sensing matrix design procedure based on compressive sensing techniques. The D-CE scheme consists of compression and decompression modules inspired by compressive sensing to perform distributed compressed estimation. A design procedure is developed under the DCE framework and a novel algorithm is developed to optimize the sensing matrix, which can further improve the performance of the proposed DCE and distributed adaptive algorithms. Simulations for a wireless sensor network show the advantages of the proposed scheme and algorithm in terms of convergence rate and mean square error performance.",
keywords = "Distributed compressed estimation, compressive sensing, sensing matrix design, sensor networks",
author = "Huang Bai and Songcen Xu and Sheng Li and {De Lamare}, {Rodrigo C.} and Xiongxiong He and Poor, {H. Vincent}",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 ; Conference date: 20-03-2016 Through 25-03-2016",
year = "2016",
month = may,
day = "18",
doi = "10.1109/ICASSP.2016.7472366",
language = "English (US)",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3691--3695",
booktitle = "2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings",
address = "United States",
}