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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,...
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...
BMCBI
2010
113views more  BMCBI 2010»
13 years 4 months ago
Probabilistic Principal Component Analysis for Metabolomic Data
Background: Data from metabolomic studies are typically complex and high-dimensional. Principal component analysis (PCA) is currently the most widely used statistical technique fo...
Gift Nyamundanda, Lorraine Brennan, Isobel Claire ...
JMLR
2012
11 years 7 months ago
Sparse Higher-Order Principal Components Analysis
Traditional tensor decompositions such as the CANDECOMP / PARAFAC (CP) and Tucker decompositions yield higher-order principal components that have been used to understand tensor d...
Genevera Allen
ICPR
2010
IEEE
13 years 6 months ago
Compressing Sparse Feature Vectors Using Random Ortho-Projections
In this paper we investigate the usage of random ortho-projections in the compression of sparse feature vectors. The study is carried out by evaluating the compressed features in ...
Esa Rahtu, Mikko Salo, Janne Heikkilä