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.
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.
Es gelten unsere Allgemeinen Geschäftsbedingungen: www.buecher.de/agb
Impressum
www.buecher.de ist ein Shop der buecher.de GmbH & Co. KG Bürgermeister-Wegele-Str. 12, 86167 Augsburg Amtsgericht Augsburg HRA 13309
