统计 | Bayesian Filtering and Smoothing

作者:阁楼君

The book is mainly intended for advanced undergraduate and graduate students in applied mathematics and computer science.

Bayesian Filtering and Smoothing



SIMO SARKKA



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The aim of this book is to give a concise introduction to non-linear Kalman filtering and smoothing, particle filtering and smoothing, and to the related parameter estimation methods. Although the book is intended to be an introduction, the mathematical ideas behind all the methods are carefully explained, and a mathematically inclined reader can get quite a deep understanding of the methods by reading the book. The book is purposely kept short for quick reading.



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