Deterministic Extraction from Weak Random Sources [electronic resource] / by Ariel Gabizon.

By:

Gabizon, Ariel [author.]

Contributor(s):

SpringerLink (Online service)

Material type: Text

TextSeries: Monographs in Theoretical Computer Science. An EATCS SeriesPublisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2011Description: XII, 148 p. online resourceContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9783642149030

Subject(s):

Additional physical formats: Printed edition:: No titleDDC classification:

004.0151 23

LOC classification:

QA75.5-76.95

Online resources:

Click here to access online

In: 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.

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Item type	Current library	Call number	Status	Date due	Barcode
E-Book	Central Library		Available		E-47064

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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