Data Acquisition through Joint Compressive Sensing and Principal Component Analysis

@article{Masiero2009DataAT,
  title={Data Acquisition through Joint Compressive Sensing and Principal Component Analysis},
  author={Riccardo Masiero and Giorgio Quer and Daniele Munaretto and Michele Rossi and Joerg Widmer and Michele Zorzi},
  journal={GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference},
  year={2009},
  pages={1-6}
}
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 techniques that we exploit to do so are Compressive Sensing (CS) and Principal Component Analysis (PCA). PCA is used to find transformations that sparsify the signal, which are required for CS to retrieve, with good approximation, the original signal from a small number of samples. Our approach dynamically adapts to non… CONTINUE READING
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