Simo Sarkka (Finland Aalto University), Arno Solin (Finland Aalto University)

Applied Stochastic Differential Equations

• Broschiertes Buch

Produktbeschreibung

This intuitive hands-on text introduces stochastic differential equations (SDEs) as motivated by applications in target tracking and medical technology, and covers their use in methodologies such as filtering, parameter estimation, and machine learning. Examples include applications of SDEs arising in physics and electrical engineering.

Produktdetails

• Institute of Mathematical Statistics Textbooks
• Verlag: Cambridge University Press
• Seitenzahl: 328
• Erscheinungstermin: 11. April 2019
• Englisch
• Abmessung: 229mm x 152mm x 18mm
• Gewicht: 488g
• ISBN-13: 9781316649466
• ISBN-10: 1316649466
• Artikelnr.: 52823464

Autorenporträt

Simo Särkkä is Associate Professor of Electrical Engineering and Automation at Aalto University, Finland, Technical Advisor at IndoorAtlas Ltd., and Adjunct Professor at Tampere University of Technology and Lappeenranta University of Technology. His research interests are in probabilistic modeling and sensor fusion for location sensing, health technology, and machine learning. He has authored over ninety peer-reviewed scientific articles as well as one book, titled Bayesian Filtering and Smoothing (Cambridge, 2013).

Inhaltsangabe

1. Introduction
2. Some background on ordinary differential equations
3. Pragmatic introduction to stochastic differential equations
4. Ito calculus and stochastic differential equations
5. Probability distributions and statistics of SDEs
6. Statistics of linear stochastic differential equations
7. Useful theorems and formulas for SDEs
8. Numerical simulation of SDEs
9. Approximation of nonlinear SDEs
10. Filtering and smoothing theory
11. Parameter estimation in SDE models
12. Stochastic differential equations in machine learning
13. Epilogue.