Sensing, compression, and recovery for WSNs: Sparse signal modeling and monitoring framework

IEEE Transactions on Wireless Communications

Volumn 11, Issue 10, 2012, Pages 3447-3461

  Quer, Giorgio ^a   Masiero, Riccardo ^b   Pillonetto, Gianluigi ^b   Rossi, Michele ^a   Zorzi, Michele ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF PADOVA   (Italy)

Author keywords

Bayesian estimation; Compressive sensing; data gathering; distributed monitoring; principal component analysis; wireless sensor networks

Indexed keywords

BAYESIAN ANALYSIS; BAYESIAN ESTIMATIONS; COMPRESSIVE SENSING; DATA GATHERING; DISTRIBUTED MONITORING; DISTRIBUTED SIGNALS; FEEDBACK CONTROL LOOPS; INTERPOLATION TECHNIQUES; LAPLACIAN DISTRIBUTION; LARGE DATASETS; NUMBER OF SAMPLES; ON-LINE ESTIMATION; PERFORMANCE LIMITS; PRINCIPAL COMPONENTS; REAL SIGNALS; REAL TIME; SELF-ADAPT; SIGNAL STATISTICS; SPARSE SIGNALS; STATISTICAL DISTRIBUTION; TEMPORAL CHARACTERISTICS; UNPREDICTABLE CHANGES;

BAYESIAN NETWORKS; ERROR STATISTICS; PRINCIPAL COMPONENT ANALYSIS; RECOVERY; SIGNAL RECONSTRUCTION;

WIRELESS SENSOR NETWORKS;

EID: 84867899154     PISSN: 15361276     EISSN: None     Source Type: Journal    
DOI: 10.1109/TWC.2012.081612.110612     Document Type: Article

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