Jianyi Lin

Pattern Statistics in Multicomponent Stochastic Models

Local results in bicomponent models

• Broschiertes Buch

Produktbeschreibung

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.

Produktdetails

• Verlag: LAP Lambert Academic Publishing
• Aufl.
• Seitenzahl: 132
• Erscheinungstermin: 30. Mai 2012
• Englisch
• Abmessung: 220mm x 150mm x 8mm
• Gewicht: 192g
• ISBN-13: 9783659119835
• ISBN-10: 3659119830
• Artikelnr.: 35942663

Autorenporträt

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.