Name
Abstract | ||
|---|---|---|
We study distributed coding of compressed sensing (CS) measurements using vector quantizer (VQ). We develop a distributed framework for realizing optimized quantizer that enables encoding CS measurements of correlated sparse sources followed by joint decoding at a fusion center. The optimality of VQ encoder-decoder pairs is addressed by minimizing the sum of mean-square errors between the sparse sources and their reconstruction vectors at the fusion center. We derive a lower-bound on the end-to-end performance of the studied distributed system, and propose a practical encoder-decoder design through an iterative algorithm. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICASSP.2014.6854844 | Acoustics, Speech and Signal Processing |
Keywords | DocType | Volume |
compressed sensing,correlation methods,mean square error methods,vector quantisation,VQ encoder-decoder pairs,compressed sensing measurement,correlated sparse sources,distributed coding,distributed quantization,encoding CS measurements,end-to-end performance,fusion center,iterative algorithm,joint decoding,mean-square error sum,reconstruction vectors,studied distributed system,vector quantizer,Compressed sensing,correlation,distributed source coding,mean square error,vector quantization | Journal | abs/1404.7666 |
ISSN | Citations | PageRank |
1520-6149 | 0 | 0.34 |
References | Authors | |
18 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amirpasha Shirazinia | 1 | 62 | 6.90 |
| Saikat Chatterjee | 2 | 24 | 5.32 |
| Mikael Skoglund | 3 | 1397 | 175.71 |