Cycle Representations of Markov Processes

Name: Cycle Representations of Markov Processes
Brand: Springer-Verlag New York Inc.
SKU: 9780387291666
Price: 580.2 RON
Availability: InStock

Autor: Sophia L. Kalpazidou

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Legare: Copertă tare

Editura: Springer-Verlag New York Inc.

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This book is a prototype providing new insight into Markovian dependence via the cycle decomposition...

Informații despre carte

Autor

Sophia L. Kalpazidou

Limbă

engleză

Legare

Carte - Copertă tare

Publicat

2006

Pagini

304

EAN

9780387291666

ISBN

0387291660

Enbook ID

01381534

Editura

Springer-Verlag New York Inc.

Greutate

1390

Dimensiuni

155 x 235 x 20

Descriere completă

This book is a prototype providing new insight into Markovian dependence via the cycle decompositions. It presents a systematic account of a class of stochastic processes known as cycle (or circuit) processes - so-called because they may be defined by directed cycles. These processes have special and important properties through the interaction between the geometric properties of the trajectories and the algebraic characterization of the Markov process. An important application of this approach is the insight it provides to electrical networks and the duality principle of networks. In particular, it provides an entirely new approach to infinite electrical networks and their applications in topics as diverse as random walks, the classification of Riemann surfaces, and to operator theory.The second edition of this book adds new advances to many directions, which reveal wide-ranging interpretations of the cycle representations like homologic decompositions, orthogonality equations, Fourier series, semigroup equations, and disintegration of measures. The versatility of these interpretations is consequently motivated by the existence of algebraic-topological principles in the fundamentals of the cycle representations. This book contains chapter summaries as well as a number of detailed illustrations.Review of the earlier edition:"This is a very useful monograph which avoids ready ways and opens new research perspectives. It will certainly stimulate further work, especially on the interplay of algebraic and geometrical aspects of Markovian dependence and its generalizations."Math Reviews.

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