Diffusion strategies for in-network principal component analysis
Nisrine Ghadban, Paul Honeiné, Farah Mourad-Chehade, Clovis Francis, Joumana Farah · 2014
This paper deals with the principal component analysis in networks, where it is improper to compute the sample covariance matrix. To this end, we derive several in-network strategies to estimate the principal axes, including noncooperative and cooperative (diffusion-based) strategies. The performance of the proposed strategies is illustrated on diverse applications, including image processing and dimensionality reduction of time series in wireless sensor networks.