Clustering Theory and Applications
Abstract
The report describes the theory for recovering information from sparse signal representations in distributed sensing applications. This theory is useful in streamlining networking and decoding operations over bandwidth constrained wireless networks. Using these results, we can for example transport and store a single combined measurement set, rather than multiple sets from all sensors. We show that via source separation and joint decoding, it is possible to recover information about the original signal from such combined measurements using progressive reconstruction. This results indicate a substantial reduction in the number of variables that are decoded at each step with a much reduced decoding time
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 01, 2012
- Accession Number
- ADA560226
Entities
People
- H. T. Kung