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Optimal quantization for distributed compressive sensing

Authors: Mehmet Yamac; Bulent Sankur; Can Altay;

Optimal quantization for distributed compressive sensing

Abstract

In large scale distributed sensing systems such as wireless sensor networks (WSNs), Distributed Source Coding Methods can be difficult to apply, due to lack of signal statistics. Distributed Compressive Sensing (DCS) emerges as a cure to this problem. Moreover, the size of the sensor reports on distributed sensing is limited due to bandwidth and battery power limitations. In this study, we investigate the optimal non-linear quantization with Lloyd-Max method for DCS under unknown signal statistics.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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