@inproceedings{10cc5ee1152d4076bbdf9cbd9bcff378,
title = "Optimal quantization for compressive sensing under message passing reconstruction",
abstract = "We consider the optimal quantization of compressive sensing measurements along with estimation from quantized samples using generalized approximate message passing (GAMP). GAMP is an iterative reconstruction scheme inspired by the belief propagation algorithm on bipartite graphs which generalizes approximate message passing (AMP) for arbitrary measurement channels. Its asymptotic error performance can be accurately predicted and tracked through the state evolution formalism. We utilize these results to design mean-square optimal scalar quantizers for GAMP signal reconstruction and empirically demonstrate the superior error performance of the resulting quantizers.",
author = "Ulugbek Kamilov and Goyal, {Vivek K.} and Sundeep Rangan",
year = "2011",
doi = "10.1109/ISIT.2011.6034168",
language = "English (US)",
isbn = "9781457705953",
series = "IEEE International Symposium on Information Theory - Proceedings",
pages = "459--463",
booktitle = "2011 IEEE International Symposium on Information Theory Proceedings, ISIT 2011",
note = "2011 IEEE International Symposium on Information Theory Proceedings, ISIT 2011 ; Conference date: 31-07-2011 Through 05-08-2011",
}