
Generalized Stochastic Processes
Modelling and Applications of Noise Processes
Stefan Schäffler(Author)
Birkhäuser (Publisher)
Published on 3. July 2018
Book
Paperback/Softback
XV, 183 pages
978-3-319-78767-1 (ISBN)
Description
This textbook shall serve a double purpose: first of all, it is a book about generalized stochastic processes, a very important but highly neglected part of probability theory which plays an outstanding role in noise modelling. Secondly, this textbook is a guide to noise modelling for mathematicians and engineers to foster the interdisciplinary discussion between mathematicians (to provide effective noise models) and engineers (to be familiar with the mathematical backround of noise modelling in order to handle noise models in an optimal way).Two appendices on "A Short Course in Probability Theory" and "Spectral Theory of Stochastic Processes" plus a well-choosen set of problems and solutions round this compact textbook off.
Reviews / Votes
"The book is written with great pedagogical care to serve as an introductory textbook for engineers on the topic of generalized stochastic processes, but it may also represent a valuable reference to a broad audience of researchers who work in the field of stochastic calculus." (Dora Selesi, zbMATH 1436.60001, 2020)
More details
Series
Edition
2018 ed.
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Illustrations
68 s/w Abbildungen, 1 farbige Abbildung
XV, 183 p. 69 illus., 1 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 12 mm
Weight
312 gr
ISBN-13
978-3-319-78767-1 (9783319787671)
DOI
10.1007/978-3-319-78768-8
Schweitzer Classification
Other editions
Additional editions

E-Book
06/2018
Birkhäuser
€53.49
Available for download
Person
Prof. Dr. Dr. Stefan Schäffler, University of the Bundeswehr Munich, Faculty of Electrical Engineering and Information Technology, Chair of Mathematics and Operations Research
Content
Generalized Functions.- Stochastic Processes.- Stochastic Differential Equations.- Generalized Random Fields.