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Bayesian Filtering and Smoothing (Institute of Mathematical Statistics Textbooks) 1st Edition

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ISBN-13: 978-1107619289
ISBN-10: 1107619289
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Bayesian Filtering and Smoothing (Institute of Mathematical Statistics Textbooks) + Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series)
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Book Description

This compact, informal introduction for graduate students and advanced undergraduates draws together modern state estimation methods including non-linear Kalman filters, particle filters, and the related smoothing algorithms. Its practical and algorithmic approach assumes only modest mathematical prerequisites. End-of-chapter exercises include computational assignments, and Matlab code is available for download.

About the Author

Simo Särkkä worked, from 2000 to 2010, with Nokia Ltd, Indagon Ltd and Nalco Company in various industrial research projects related to telecommunications, positioning systems and industrial process control. Currently, he is a Senior Researcher with the Department of Biomedical Engineering and Computational Science at Aalto University, Finland, and Adjunct Professor with Tampere University of Technology and Lappeenranta University of Technology. In 2011 he was a visiting scholar with the Signal Processing and Communications Laboratory of the Department of Engineering at the University of Cambridge. His research interests are in state and parameter estimation in stochastic dynamic systems, and in particular, Bayesian methods in signal processing, machine learning, and inverse problems with applications to brain imaging, positioning systems, computer vision and audio signal processing. He is a Senior Member of IEEE.

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Product Details

  • Series: Institute of Mathematical Statistics Textbooks (Book 3)
  • Paperback: 252 pages
  • Publisher: Cambridge University Press; 1 edition (October 21, 2013)
  • Language: English
  • ISBN-10: 1107619289
  • ISBN-13: 978-1107619289
  • Product Dimensions: 6 x 0.5 x 9 inches
  • Shipping Weight: 14.9 ounces (View shipping rates and policies)
  • Average Customer Review: 4.5 out of 5 stars  See all reviews (2 customer reviews)
  • Amazon Best Sellers Rank: #1,026,189 in Books (See Top 100 in Books)

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1 of 1 people found the following review helpful By K. Hicks on March 4, 2014
Format: Paperback Verified Purchase
I bought this because it is one of the few books I've seen that spells out the extended RTS filter. Nice explanation. This author has some lecture notes up on the web, and they go nicely with this book. The price is great. The only downside I found is that it could use a few COMPLETE examples. Most are set up and then graphical results given. I'd like to see a few more intermediate steps or results. Like my title says, the notation is a little different than I've seen in other books, but that shouldn't slow you down too much.
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1 of 1 people found the following review helpful By Evandro Luiz da Costa on November 13, 2013
Format: Hardcover Verified Purchase
Very comprehensive. It is a very updated book, covering most of the main methods used today. It does not go into the details, it's more like a reference book.
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