Pattern Statistics in Multicomponent Stochastic Models | Local results in bicomponent models

Jianyi Lin

ISBN 10: 3659119830 ISBN 13: 9783659119835
Editorial: LAP LAMBERT Academic Publishing, 2012
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Descripción:

Pattern Statistics in Multicomponent Stochastic Models | Local results in bicomponent models | Jianyi Lin | Taschenbuch | 132 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783659119835 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de ref. del artículo 106425705

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Sinopsis:

The study of symbol frequencies in randomly generated words is an issue related to various research areas of the computational sciences, such as bioinformatics, telecommunication code synchronisation, algorithm analysis, and meets its first motivations in the context of molecular biology, mainly in the analysis of genomic DNA sequences. The central question consists in evaluating in probabilistic terms the occurrences of given patterns, defined over a finite alphabet, within a word formed over the same alphabet and randomly generated from a suitable stochastic source. Several models have been proposed in literature to describe this system, such as the Bernoulli process, in which all symbol occurrences are statistically independent from each other, and the Markov process, in which a symbol occurrence depends only on the preceding symbol. This work investigates a bicomponent extension defined by a rational formal series with non-commutative variables over the semi-ring of positive reals, called rational stochastic model, whose certain conditions of periodicity, matrix reducibility, dominance and degeneracy yield various local and integral limit properties on pattern distributions.

Reseña del editor: The study of symbol frequencies in randomly generated words is an issue related to various research areas of the computational sciences, such as bioinformatics, telecommunication code synchronisation, algorithm analysis, and meets its first motivations in the context of molecular biology, mainly in the analysis of genomic DNA sequences. The central question consists in evaluating in probabilistic terms the occurrences of given patterns, defined over a finite alphabet, within a word formed over the same alphabet and randomly generated from a suitable stochastic source. Several models have been proposed in literature to describe this system, such as the Bernoulli process, in which all symbol occurrences are statistically independent from each other, and the Markov process, in which a symbol occurrence depends only on the preceding symbol. This work investigates a bicomponent extension defined by a rational formal series with non-commutative variables over the semi-ring of positive reals, called rational stochastic model, whose certain conditions of periodicity, matrix reducibility, dominance and degeneracy yield various local and integral limit properties on pattern distributions.

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Detalles bibliográficos

Título: Pattern Statistics in Multicomponent ...
Editorial: LAP LAMBERT Academic Publishing
Año de publicación: 2012
Encuadernación: Taschenbuch
Condición: Neu

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