Recursive nonlinear estimation : a geometric approach /
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Author / Creator: | Kulhavý, Rudolf, 1957- |
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Imprint: | Berlin ; New York : Springer, ©1996. |
Description: | 1 online resource (xvi, 224 pages) : illustrations. |
Language: | English |
Series: | Lecture notes in control and information sciences ; 216 Lecture notes in control and information sciences ; 216. |
Subject: | |
Format: | E-Resource Book |
URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/11073820 |
ISBN: | 9783540409472 3540409475 3540760636 9783540760634 |
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Notes: | Includes bibliographical references (pages 213-222) and index. Restrictions unspecified Electronic reproduction. [S.l.] : HathiTrust Digital Library, 2010. Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. http://purl.oclc.org/DLF/benchrepro0212 digitized 2010 HathiTrust Digital Library committed to preserve Print version record. |
Summary: | In a close analogy to matching data in Euclidean space, this monograph views parameter estimation as matching of the empirical distribution of data with a model-based distribution. Using an appealing Pythagorean-like geometry of the empirical and model distributions, the book brings a new solution to the problem of recursive estimation of non-Gaussian and nonlinear models which can be regarded as a specific approximation of Bayesian estimation. The cases of independent observations and controlled dynamic systems are considered in parallel; the former case giving initial insight into the latter case which is of primary interest to the control community. A number of examples illustrate the key concepts and tools used. This unique monograph follows some previous results on the Pythagorean theory of estimation in the literature (e.g., Chentsov, Csiszar and Amari) but extends the results to the case of controlled dynamic systems. |
Other form: | Print version: Kulhavý, Rudolf, 1957- Recursive nonlinear estimation. Berlin ; New York : Springer, ©1996 |
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