Compressed sensing: CS for networked data, Diffusion wavelets and Analog CS measurements.

The Special Issue on Compressive Sampling of the IEEE Signal Processing Magazine will also feature Compressed sensing for networked data by Jarvis Haupt, Waheed Bajwa, Mike Rabbat, and Robert Nowak. In the article, one can learn how one can exploit the connectivity in the network "as the key to obtaining effective sparsifying transformations for networked data". Hence because Network traffic patterns are sparse in the diffusion wavelet framework, the idea is to use this framework to enable Compressed Sensing measurements from networks.


They also discuss the specific schemes one could implement with a particular attention to data from wireless networks and the analog production of the compressed sensing data through the use of the network. Very nice.