Deterministic Extraction from Weak Random Sources [electronic resource] / by Ariel Gabizon.
By: Gabizon, Ariel [author.].
Contributor(s): SpringerLink (Online service).
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BookSeries: Monographs in Theoretical Computer Science. An EATCS Series: Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2011Description: XII, 148 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642149030.Subject(s): Computer science | Information theory | Geometry, algebraic | Combinatorics | Computer Science | Theory of Computation | Mathematics of Computing | Algebraic Geometry | CombinatoricsDDC classification: 004.0151 Online resources: Click here to access online
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Springer eBooksSummary: A deterministic extractor is a function that extracts almost perfect random bits from a weak random source. In this research monograph the author constructs deterministic extractors for several types of sources. A basic theme in this work is a methodology of recycling randomness which enables increasing the output length of deterministic extractors to near optimal length. The author's main work examines deterministic extractors for bit-fixing sources, deterministic extractors for affine sources and polynomial sources over large fields, and increasing the output length of zero-error dispersers. This work will be of interest to researchers and graduate students in combinatorics and theoretical computer science.
A deterministic extractor is a function that extracts almost perfect random bits from a weak random source. In this research monograph the author constructs deterministic extractors for several types of sources. A basic theme in this work is a methodology of recycling randomness which enables increasing the output length of deterministic extractors to near optimal length. The author's main work examines deterministic extractors for bit-fixing sources, deterministic extractors for affine sources and polynomial sources over large fields, and increasing the output length of zero-error dispersers. This work will be of interest to researchers and graduate students in combinatorics and theoretical computer science.
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