almediah.fr
» » Probabilistic Methods in Combinatorial Analysis (Encyclopedia of Mathematics and its Applications)

Download Probabilistic Methods in Combinatorial Analysis (Encyclopedia of Mathematics and its Applications) eBook

by Vladimir N. Sachkov,V. A. Vatutin

Download Probabilistic Methods in Combinatorial Analysis (Encyclopedia of Mathematics and its Applications) eBook
ISBN:
0521172772
Author:
Vladimir N. Sachkov,V. A. Vatutin
Category:
Mathematics
Language:
English
Publisher:
Cambridge University Press; Reissue edition (February 17, 2011)
Pages:
258 pages
EPUB book:
1835 kb
FB2 book:
1859 kb
DJVU:
1793 kb
Other formats
docx mbr txt rtf
Rating:
4.1
Votes:
760


This work explores the role of probabilistic methods for solving combinatorial problems.

This work explores the role of probabilistic methods for solving combinatorial problems.

Cambridge Core - Discrete Mathematics Information Theory and Coding - Probabilistic Methods in. .Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications, Vol. 2003, Issue.

Cambridge Core - Discrete Mathematics Information Theory and Coding - Probabilistic Methods in Combinatorial Analysis - by Vladimir N. Sachkov.

by Vladimir N. Sachkov (Author), V. A. Vatutin (Translator). Books Science, Nature & Math Mathematics Pure Mathematics. Books Textbooks & Study Guides.

combinatorial mathematics, combinatorics. The branch of mathematics devoted to the solution of problems of choosing and arranging the elements of certain (usually finite) sets in accordance with prescribed rules. Each such rule defines a method of constructing some configuration of elements of the given set, called a combinatorial configuration. One can therefore say that the aim of combinatorial analysis is the study of combinatorial configurations

Автор: Sachkov Название: Probabilistic Methods in Combinatorial Analysis ISBN: 0521172772 ISBN-13 .

Описание: This 1997 work explores the role of probabilistic methods for solving combinatorial problems. This book covers topics including combinatorial image analysis; grammars and models for analysis and recognition of scenes and images; and combinatorial topology and geometry for images.

Start by marking Probabilistic Methods in Combinatorial Analysis as Want to Read .

Start by marking Probabilistic Methods in Combinatorial Analysis as Want to Read: Want to Read savin. ant to Read.

The probabilistic method is a nonconstructive method, primarily used in combinatorics and pioneered by Paul Erdős, for proving the existence of a prescribed kind of mathematical object. It works by showing that if one randomly chooses objects from a specified class, the probability that the result is of the prescribed kind is strictly greater than zero. Although the proof uses probability, the final conclusion is determined for certain, without any possible error.

Vladimir N. Sachkov, Combinatorial methods in discrete mathematics, Encyclopedia of Mathematics and its Applications, vol. 55, Cambridge University Press, 1996. 126. Arto Salomaa and Matti Soittola, Automata-theoretic aspects of formal power series, Springer, Berlin, 1978. 130. Robert Sedgewick and Philippe Flajolet, An introduction to the analysis of algorithms, Addison-Wesley Publishing Company, 1996.

Categories: Discrete Mathematics. By (author) Sachkov Vladimir N, By (author) Vladimir N Sachkov, Translated by Vatutin V a, Translated by V A Vatutin. Probability & Statistics. Probabilistic Methods in Combinatorial Analysis. We can notify you when this item is back in stock. AbeBooks may have this title (opens in new window).

1 result for Books : "Probabilistic methods in combinatorial analysis Vladimir N. Sachkov, V. Vatutin". Probabilistic methods in combinatorial analysis Vladimir N. Probabilistic Methods in Combinatorial Analysis (Encyclopedia of Mathematics and its Applications). by Vladimir N. Sachkov and V. Vatutin.

This work explores the role of probabilistic methods for solving combinatorial problems. The subjects studied are nonnegative matrices, partitions and mappings of finite sets, with special emphasis on permutations and graphs, and equivalence classes specified on sequences of finite length consisting of elements of partially ordered sets; these define the probabilistic setting of Sachkov's general combinatorial scheme. The author pays special attention to using probabilistic methods to obtain asymptotic formulae that are difficult to derive using combinatorial methods. This important book describes many ideas not previously available in English and will be of interest to graduate students and professionals in mathematics and probability theory.