Predictive and filtering lower bounds for nonlinear filters
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F99%3A00042797" target="_blank" >RIV/49777513:23520/99:00042797 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Predictive and filtering lower bounds for nonlinear filters
Original language description
The idea of utilizing Cramer-Rao lower bounds for performance evaluation of filters for nonlinear discrete-time stochastic systems with Gaussian disturbances is followed. Lower bounds for mean-square errors of filtering, one-step and multi-step predictivestimates are derived in the form of recursive relations. Two different ways of estimating mean-square error matrices based on Monte Carlo simulations are introduced and confronted with Cramer-Rao bounds. Evaluation of estimation quality is demonstratedby a numerical example.
Czech name
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Czech description
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Classification
Type
C - Chapter in a specialist book
CEP classification
BC - Theory and management systems
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
1999
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Book/collection name
Predictive and filtering lower bounds for nonlinear filters
ISBN
0080432190
Number of pages of the result
6
Pages from-to
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Number of pages of the book
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Publisher name
Elsevier Science
Place of publication
Oxford
UT code for WoS chapter
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