Bayesian filtering and smoothing (Record no. 378256)

MARC details
000 -LEADER
fixed length control field 01805 a2200205 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 140323b2013 xxu||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781107619289
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Item number S2B2
Classification number 519.542
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Sarkka, Simo
9 (RLIN) 97299
245 ## - TITLE STATEMENT
Title Bayesian filtering and smoothing
Statement of responsibility, etc. Sarkka, Simo
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Date of publication, distribution, etc. 2013
Name of publisher, distributor, etc. Cambridge University Press
Place of publication, distribution, etc. New York
300 ## - PHYSICAL DESCRIPTION
Extent xxii, 232 p.
365 ## - TRADE PRICE
Price type code UKP
Price amount 21.99
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Institute of Mathematical Statistics Textbooks
9 (RLIN) 250705
520 ## - SUMMARY, ETC.
Summary, etc. Filtering and smoothing methods are used to produce an accurate estimate of the state of a time-varying system based on multiple observational inputs (data). Interest in these methods has exploded in recent years, with numerous applications emerging in fields such as navigation, aerospace engineering, telecommunications and medicine. This compact, informal introduction for graduate students and advanced undergraduates presents the current state-of-the-art filtering and smoothing methods in a unified Bayesian framework. Readers learn what non-linear Kalman filters and particle filters are, how they are related, and their relative advantages and disadvantages. They also discover how state-of-the-art Bayesian parameter estimation methods can be combined with state-of-the-art filtering and smoothing algorithms. The book's practical and algorithmic approach assumes only modest mathematical prerequisites. Examples include MATLAB computations, and the numerous end-of-chapter exercises include computational assignments. MATLAB/GNU Octave source code is available for download at www.cambridge.org/sarkka, promoting hands-on work with the methods.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Bayesian statistical decision theory
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Filters (Mathematics)
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Smoothing (Statistics)
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Book
Holdings
Withdrawn status Lost status Damaged status Not for loan Collection code Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Total Checkouts Total Renewals Full call number Barcode Date last seen Date last checked out Cost, replacement price Price effective from Koha item type
        Non-fiction Ahmedabad Ahmedabad   25/11/2013 13 1845.40 2 2 519.542 S2B2 180313 10/08/2015 06/10/2014 2306.75 22/11/2013 Book

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