Pattern Statistics in Multicomponent Stochastic Models: Local results in bicomponent models - Softcover
Synopsis
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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About the Author
Jianyi Lin graduated in Computing Systems Engineering at Politecnico di Milano and is a PhD Fellow in Computational Mathematics at the University of Milan. His main research topics consist of pattern statistics in stochastic models, biomechanics and neurocomputing, industrial process control and computational complexity of geometric clustering.
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Pattern Statistics in Multicomponent Stochastic Models
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 132 pp. Englisch. Seller Inventory # 9783659119835
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Pattern Statistics in Multicomponent Stochastic Models
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Lin JianyiJianyi Lin graduated in Computing Systems Engineering at Politecnico di Milano and is a PhD Fellow in Computational Mathematics at the University of Milan. His main research topics consist of pattern statistics in stochasti. Seller Inventory # 5132746
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Pattern Statistics in Multicomponent Stochastic Models
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ISBN 10: 3659119830
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 132 pp. Englisch. Seller Inventory # 9783659119835
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Pattern Statistics in Multicomponent Stochastic Models : Local results in bicomponent models
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ISBN 13: 9783659119835
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Seller Inventory # 9783659119835
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Pattern Statistics in Multicomponent Stochastic Models: Local results in bicomponent models
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