Almost Periodic Stochastic Processes

Name: Almost Periodic Stochastic Processes
Brand: Springer-Verlag New York Inc.
SKU: 9781441994752
Price: 2567 CZK
Availability: InStock

Autor: Paul H. Bezandry, Toka Diagana

Jazyk:

Vazba: Pevná

Vydavatel: Springer-Verlag New York Inc.

Dostupnost: Skladem u dodavatele v malém množství

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2 567 Kč

Almost Periodic Stochastic Processes is among the few published books that is entirely devoted to al...

Informace o knize

Autor

Paul H. Bezandry, Toka Diagana

Jazyk

Angličtina

Vazba

Kniha - Pevná

Vydáno

2011

Stránek

235

EAN

9781441994752

ISBN

1441994750

Enbook ID

01424528

Vydavatel

Springer-Verlag New York Inc.

Hmotnost

520

Rozměry

247 x 165 x 19

Kompletní popis

Almost Periodic Stochastic Processes is among the few published books that is entirely devoted to almost periodic stochastic processes and their applications. The topics treated range from existence, uniqueness, boundedness, and stability of solutions, to stochastic difference and differential equations. Motivated by the studies of the natural fluctuations in nature, this work aims to lay the foundations for a theory on almost periodic stochastic processes and their applications.This book is divided in to eight chapters and offers useful bibliographical notes at the end of each chapter. Highlights of this monograph include the introduction of the concept of p-th mean almost periodicity for stochastic processes and applications to various equations. The book offers some original results on the boundedness, stability, and existence of p-th mean almost periodic solutions to (non)autonomous first and/or second order stochastic differential equations, stochastic partial differential equations, stochastic functional differential equations with delay, and stochastic difference equations. Various illustrative examples are also discussed throughout the book.The results provided in the book will be of particular use to those conducting research in the field of stochastic processing including engineers, economists, and statisticians with backgrounds in functional analysis and stochastic analysis. Advanced graduate students with backgrounds in real analysis, measure theory, and basic probability, may also find the material in this book quite useful and engaging.

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