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Democracy in action: Quantization, s...

Laska, Jason N.

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Democracy in action: Quantization, saturation, and compressive sensing.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Democracy in action: Quantization, saturation, and compressive sensing./
Author:	Laska, Jason N.
Description:	66 p.
Notes:	Source: Masters Abstracts International, Volume: 49-01, page: 0581.
Contained By:	Masters Abstracts International49-01.
Subject:	Engineering, Computer. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1486023
ISBN:	9781124213330

Democracy in action: Quantization, saturation, and compressive sensing.
Laska, Jason N.

Democracy in action: Quantization, saturation, and compressive sensing. - 66 p.

Source: Masters Abstracts International, Volume: 49-01, page: 0581.

Thesis (M.S.)--Rice University, 2010.

We explore and exploit a heretofore relatively unexplored hallmark of compressive sensing (CS), the fact that certain CS measurement systems are democratic, which means that each measurement carries roughly the same amount of information about the signal being acquired. Using this property, we re-think how to quantize the compressive measurements. In Shannon-Nyquist sampling, we scale down the analog signal amplitude (and therefore increase the quantization error) to avoid the gross saturation errors. In stark contrast, we demonstrate a CS system achieves the best performance when we operate at a significantly nonzero saturation rate. We develop two methods to recover signals from saturated CS measurements. The first directly exploits the democracy property by simply discarding the saturated measurements. The second integrates saturated measurements as constraints into standard linear programming and greedy recovery techniques. Finally, we develop a simple automatic gain control system that uses the saturation rate to optimize the input gain.

ISBN: 9781124213330Subjects--Topical Terms:

1669061
Engineering, Computer.

Democracy in action: Quantization, saturation, and compressive sensing.
LDR:01916nam 2200277 4500 001 1403250
005 20111111141847.5
008 130515s2010 ||||||||||||||||| ||eng d
020 $a 9781124213330
035 $a (UMI)AAI1486023
035 $a AAI1486023
040 $a UMI $c UMI
100 1 $a Laska, Jason N. $3 1682505
245 1 0 $a Democracy in action: Quantization, saturation, and compressive sensing.
300 $a 66 p.
500 $a Source: Masters Abstracts International, Volume: 49-01, page: 0581.
500 $a Adviser: Richard G. Baraniuk.
502 $a Thesis (M.S.)--Rice University, 2010.
520 $a We explore and exploit a heretofore relatively unexplored hallmark of compressive sensing (CS), the fact that certain CS measurement systems are democratic, which means that each measurement carries roughly the same amount of information about the signal being acquired. Using this property, we re-think how to quantize the compressive measurements. In Shannon-Nyquist sampling, we scale down the analog signal amplitude (and therefore increase the quantization error) to avoid the gross saturation errors. In stark contrast, we demonstrate a CS system achieves the best performance when we operate at a significantly nonzero saturation rate. We develop two methods to recover signals from saturated CS measurements. The first directly exploits the democracy property by simply discarding the saturated measurements. The second integrates saturated measurements as constraints into standard linear programming and greedy recovery techniques. Finally, we develop a simple automatic gain control system that uses the saturation rate to optimize the input gain.
590 $a School code: 0187.
650 4 $a Engineering, Computer. $3 1669061
650 4 $a Engineering, Electronics and Electrical. $3 626636
690 $a 0464
690 $a 0544
710 2 $a Rice University. $3 960124
773 0 $t Masters Abstracts International $g 49-01.
790 1 0 $a Baraniuk, Richard G., $e advisor
790 $a 0187
791 $a M.S.
792 $a 2010
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1486023