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ICUMT
2009
13 years 4 months ago
A Bayesian analysis of Compressive Sensing data recovery in Wireless Sensor Networks
Abstract--In this paper we address the task of accurately reconstructing a distributed signal through the collection of a small number of samples at a data gathering point using Co...
Riccardo Masiero, Giorgio Quer, Michele Rossi, Mic...
GLOBECOM
2009
IEEE
14 years 1 months ago
Data Acquisition through Joint Compressive Sensing and Principal Component Analysis
—In this paper we look at the problem of accurately reconstructing distributed signals through the collection of a small number of samples at a data gathering point. The techniqu...
Riccardo Masiero, Giorgio Quer, Daniele Munaretto,...
TSP
2010
13 years 28 days ago
Decentralized sparse signal recovery for compressive sleeping wireless sensor networks
Abstract--This paper develops an optimal decentralized algorithm for sparse signal recovery and demonstrates its application in monitoring localized phenomena using energy-constrai...
Qing Ling, Zhi Tian
PERCOM
2010
ACM
13 years 4 months ago
Resilient image sensor networks in lossy channels using compressed sensing
—Data loss in wireless communications greatly affects the reconstruction quality of a signal. In the case of images, data loss results in a reduction in quality of the received i...
Scott Pudlewski, Arvind Prasanna, Tommaso Melodia
DCOSS
2009
Springer
13 years 11 months ago
Compressed RF Tomography for Wireless Sensor Networks: Centralized and Decentralized Approaches
Radio Frequency (RF) tomography refers to the process of inferring information about an environment by capturing and analyzing RF signals transmitted between nodes in a wireless se...
Mohammad A. Kanso, Michael G. Rabbat