Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top

2018 | Book

Generalized Functions Read chapter Read first chapter

Generalized Stochastic Processes

Modelling and Applications of Noise Processes

Author: Prof. Stefan Schäffler

Publisher: Springer International Publishing

Book Series : Compact Textbooks in Mathematics

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Wirtschaft"

Login to get access
insite
SEARCH

About this book

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.

Table of Contents

Frontmatter
1. Generalized Functions
Abstract
On the real valued spaces \(\mathbb {R}^n\), \(n \in \mathbb {N}\), we use the Euclidean norm .
Stefan Schäffler
2. Stochastic Processes
Abstract
Let \((\varOmega, {\mathcal {S}}, \mathbb {P})\) be a probability space. Each probability space is a model for a random experiment with a nonempty set Ω of the possible results .
Stefan Schäffler
3. Stochastic Differential Equations
Abstract
Considering the capacitor voltage U c in an LRC circuit (see ⊡ Fig. 3.1).
Stefan Schäffler
4. Generalized Random Fields
Abstract
Let \((\varOmega , {\mathcal {S}},\mathbb {P})\) be a probability space and let \((H, {\mathcal {H}},\mu )\) be a measure space.
Stefan Schäffler
Backmatter
Metadata
Title
Generalized Stochastic Processes
Author
Prof. Stefan Schäffler
Copyright Year
2018
Electronic ISBN
978-3-319-78768-8
Print ISBN
978-3-319-78767-1
DOI
https://doi.org/10.1007/978-3-319-78768-8