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ICUMT
2009
13 years 2 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
13 years 11 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
12 years 11 months 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 3 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 9 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