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Applied Stochastic Differential Equations
Buch von Simo Särkkä
Sprache: Englisch

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Beschreibung
With this hands-on introduction readers will learn what SDEs are all about and how they should use them in practice.
With this hands-on introduction readers will learn what SDEs are all about and how they should use them in practice.
Über den Autor
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).
Inhaltsverzeichnis
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.
Details
Erscheinungsjahr: 2019
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
ISBN-13: 9781316510087
ISBN-10: 1316510085
Sprache: Englisch
Ausstattung / Beilage: HC gerader Rücken kaschiert
Einband: Gebunden
Autor: Särkkä, Simo
Hersteller: Cambridge University Press
Maße: 235 x 157 x 22 mm
Von/Mit: Simo Särkkä
Erscheinungsdatum: 02.05.2019
Gewicht: 0,629 kg
Artikel-ID: 113912890
Über den Autor
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).
Inhaltsverzeichnis
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.
Details
Erscheinungsjahr: 2019
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
ISBN-13: 9781316510087
ISBN-10: 1316510085
Sprache: Englisch
Ausstattung / Beilage: HC gerader Rücken kaschiert
Einband: Gebunden
Autor: Särkkä, Simo
Hersteller: Cambridge University Press
Maße: 235 x 157 x 22 mm
Von/Mit: Simo Särkkä
Erscheinungsdatum: 02.05.2019
Gewicht: 0,629 kg
Artikel-ID: 113912890
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