A Course in Applied Stochastic Processes

A Course in Applied Stochastic Processes
Author :
Publisher : Springer
Total Pages : 226
Release :
ISBN-10 : 9789386279316
ISBN-13 : 9386279312
Rating : 4/5 (16 Downloads)

Book Synopsis A Course in Applied Stochastic Processes by : A. Goswami

Download or read book A Course in Applied Stochastic Processes written by A. Goswami and published by Springer. This book was released on 2006-09-15 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt:


A Course in Applied Stochastic Processes Related Books

A Course in Applied Stochastic Processes
Language: en
Pages: 226
Authors: A. Goswami
Categories: Mathematics
Type: BOOK - Published: 2006-09-15 - Publisher: Springer

DOWNLOAD EBOOK

Basics of Applied Stochastic Processes
Language: en
Pages: 452
Authors: Richard Serfozo
Categories: Mathematics
Type: BOOK - Published: 2009-01-24 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

Stochastic processes are mathematical models of random phenomena that evolve according to prescribed dynamics. Processes commonly used in applications are Marko
Stochastic Processes and Applications
Language: en
Pages: 345
Authors: Grigorios A. Pavliotis
Categories: Mathematics
Type: BOOK - Published: 2014-11-19 - Publisher: Springer

DOWNLOAD EBOOK

This book presents various results and techniques from the theory of stochastic processes that are useful in the study of stochastic problems in the natural sci
Applied Stochastic Processes
Language: en
Pages: 209
Authors: Ming Liao
Categories: Business & Economics
Type: BOOK - Published: 2013-07-22 - Publisher: CRC Press

DOWNLOAD EBOOK

Applied Stochastic Processes presents a concise, graduate-level treatment of the subject, emphasizing applications and practical computation. It also establishe
Applied Stochastic Processes
Language: en
Pages: 395
Authors: Mario Lefebvre
Categories: Mathematics
Type: BOOK - Published: 2007-12-14 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

This book uses a distinctly applied framework to present the most important topics in stochastic processes, including Gaussian and Markovian processes, Markov C