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100513t20102010riua b 001 0 eng |
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|a 2010018152
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|a 015658372
|2 Uk
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|a 9780821851920 (alk. paper)
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|a 0821851926 (alk. paper)
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|a (OCoLC)615339073
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|a DLC
|b eng
|c DLC
|d YDX
|d YDXCP
|d CDX
|d UKMGB
|d SFB
|d MUU
|d OCLCF
|d S3O
|d EEM
|d UtOrBLW
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|a EEMR
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|a QA267.7
|b .G654 2010
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|a 004.01/51
|2 22
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1 |
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|a Goldreich, Oded.
|0 http://id.loc.gov/authorities/names/n98097979
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|a A primer on pseudorandom generators /
|c Oded Goldreich.
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|a Providence, R.I. :
|b American Mathematical Society,
|c [2010], ©2010.
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300 |
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|a x, 114 pages :
|b illustrations ;
|c 26 cm.
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336 |
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|a text
|b txt
|2 rdacontent
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|a unmediated
|b n
|2 rdamedia
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|a volume
|b nc
|2 rdacarrier
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490 |
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|a University lecture series ;
|v v. 55
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504 |
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|a Includes bibliographical references and index.
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|a Chapter 1. Introduction -- Chapter 2. General-purpose pseudorandom generators -- Chapter 3. Derandomization of time-complexity classes -- Chapter 4. Space-bounded distinguishers -- Chapter 5. Special purpose generators -- Concluding remarks -- Appendix A. Hashing functions -- Appendix B. On randomness extractors -- Appendix C. A generic hard-core predicate -- Appendix D. Using randomness in computation -- Appendix E. Cryptographic applications of pseudorandom functions -- Appendix F. Some basic complexity classes.
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|a A fresh look at the question of randomness was taken in the theory of computing: A distribution is pseudorandom if it cannot be distinguished from the uniform distribution by any efficient procedure. This paradigm, originally associating efficient procedures with polynomial-time algorithms, has been applied with respect to a variety of natural classes of distinguishing procedures. The resulting theory of pseudorandomness is relevant to science at large and is closely related to central areas of computer science, such as algorithmic design, complexity theory, and cryptography.
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|a This primer surveys the theory of pseudorandomness, starting with the general paradigm, and discussing various incarnations while emphasizing the case of general-purpose pseudorandom generators (withstanding any polynomial-time distinguisher). Additional topics include the "derandomization" of arbitrary probabilistic polynomial-time algorithms, pseudorandom generators withstanding space-bounded distinguishers, and serveral natural notions of special-purpose pseudorandom generators.
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|a The primer assumes basic familiarity with the notion of efficient algorithms and with elementary probability theory, but provides a basic introduction to all notions that are actually used. as a result, the primer is essentially self-contained, although the interested reader is at times referred to other sources for more detail. --Book Jacket.
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|a Computational complexity.
|0 http://id.loc.gov/authorities/subjects/sh85029473
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|a Random number generators.
|0 http://id.loc.gov/authorities/subjects/sh85111351
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|a Computer science
|x Mathematics.
|0 http://id.loc.gov/authorities/subjects/sh85042295
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|a Computational complexity.
|2 fast
|0 (OCoLC)fst00871991
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|a Computer science
|x Mathematics.
|2 fast
|0 (OCoLC)fst00872460
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|a Random number generators.
|2 fast
|0 (OCoLC)fst01089807
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|a Datavetenskap.
|2 sao
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|a University lecture series (Providence, R.I.) ;
|v 55.
|0 http://id.loc.gov/authorities/names/n88540797
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|y .b121577326
|b 170816
|c 170213
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|a rs
|b 170213
|c m
|d a
|e -
|f eng
|g riu
|h 2
|i 2
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|t 0
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952 |
f |
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|p Can Circulate
|a Michigan State University-Library of Michigan
|b Michigan State University
|c MSU Remote Storage
|d MSU Remote Storage
|t 0
|e QA267.7 .G654 2010
|h Library of Congress classification
|i Printed Material
|m 31293035334329
|n 1
|