Applied Stochastic Differential Equations

Applied Stochastic Differential Equations

Regular price
Checking stock...
Regular price
Checking stock...
Zusammenfassung

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.

The feel-good place to buy books
  • Free delivery in the UK
  • Supporting authors with AuthorSHARE
  • 100% recyclable packaging
  • B Corp - kinder to people and planet
  • Buy-back with World of Books - Sell Your Books

Applied Stochastic Differential Equations by Arno Solin

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.
'Stochastic differential equations have long been used by physicists and engineers, especially in filtering and prediction theory, and more recently have found increasing application in the life sciences, finance and an ever-increasing range of fieldsThe authors provide intended users with an intuitive, readable introduction and overview without going into technical mathematical details from the often-demanding theory of stochastic analysis, yet clearly pointing out the pitfalls that may arise if its distinctive differences are disregarded. A large part of the book deals with underlying ideas and methods, such as analytical, approximative and computational, which are illustrated through many insightful examples. Linear systems, especially with additive noise and Gaussian solutions, are emphasized, though nonlinear systems are not neglected, and a large number of useful results and formulas are given. The latter part of the book provides an up to date survey and comparison of filtering and parameter estimation methods with many representative algorithms, and culminates with their application to machine learning.' Peter Kloeden, Johann Wolfgang Goethe-Universität Frankfurt am Main
'Overall, this is a very well-written and excellent introductory monograph to SDEs, covering all important analytical properties of SDEs, and giving an in-depth discussion of applied methods useful in solving various real-life problems.' Igor Cialenco, MathSciNet
'Chapters are rich in examples, numerical simulations, illustrations, derivations and computational assignment' Martin Ondreját, the European Mathematical Society and the Heidelberg Academy of Sciences and Humanities
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). Arno Solin is an Academy of Finland Postdoctoral Researcher with Aalto University, Finland and Technical Advisor at IndoorAtlas Ltd. His research interests focus on models and applications in sensor fusion for tracking and navigation, brain imaging, and machine learning problems. He has published over twenty peer-reviewed scientific papers, and has won several hackathons and competitions in mathematical modeling, including the 2014 Schizophrenia classification on Kaggle.
SKU Nicht verfügbar
ISBN 13 9781316649466
ISBN 10 1316649466
Titel Applied Stochastic Differential Equations
Autor Arno Solin
Serie Institute Of Mathematical Statistics Textbooks
Buchzustand Nicht verfügbar
Bindungsart Paperback
Verlag Cambridge University Press
Erscheinungsjahr 2019-05-02
Seitenanzahl 326
Hinweis auf dem Einband Die Abbildung des Buches dient nur Illustrationszwecken, die tatsächliche Bindung, das Cover und die Auflage können sich davon unterscheiden.
Hinweis Nicht verfügbar