Abstract
Deterministic randomness extractors are functions E: {0, 1}4 → {0, 1}m which refine imperfect sources of randomness in the following sense: For every probability distribution X in some "interesting family" of distributions over {0, 1}n, applying E on a sample from X yields a distribution that is (close to) the uniform distribution. Randomness extractors have many applications in various areas of computer science. Recently, Shpilka [Shp13] showed how to apply randomness extractors to solve problems in the area of data storage. Following work by Shpilka [Shp14] and Gabizon and Shaltiel [GS12b] build on this connection and extend Shpilka's original paper. In this article, we give some relevant background on randomness extractors and explain how extractors (and closely related dispersers) can be applied to solve problems in data storage.
Original language | English |
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Title of host publication | 2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781479959877 |
DOIs | |
State | Published - 2014 |
Event | 2014 28th IEEE Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014 - Eilat, Israel Duration: 3 Dec 2014 → 5 Dec 2014 |
Publication series
Name | 2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014 |
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Conference
Conference | 2014 28th IEEE Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014 |
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Country/Territory | Israel |
City | Eilat |
Period | 3/12/14 → 5/12/14 |
Bibliographical note
Publisher Copyright:© Copyright 2015 IEEE All rights reserved.
ASJC Scopus subject areas
- Electrical and Electronic Engineering