Derivatives in optimal state-estimation of singular systems

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F01%3A00064771" target="_blank" >RIV/49777513:23520/01:00064771 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Derivatives in optimal state-estimation of singular systems
Original language description
The problems of system identification or estimation of non-measurable inner system variables are very important subjects not only in the field of cybernetics. These tasks enable studying and modelling real processes in terms of abstract cybernetic systems. As the most general model of a real system has become the stochastic causal (abstract) system unambiguously defined in recently submitted new approach to system theory. The estimation of stochastic linear system unknown state variables is generally known as the Kalman filtering, provided the matrices of stochastic signals are non-singular. Both non-singular and especially singular systems are considered in this paper. The obtained results provide a certain modification of Kalman filter consisting inthe usage of a wider class of systems.
Czech name
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Czech description
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Publication year
2001
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Derivatives in optimal state-estimation of singular systems
ISBN
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ISSN
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e-ISSN
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Number of pages
6
Pages from-to
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Publisher name
Neuveden
Place of publication
Neuveden
Event location
Neuveden
Event date
Jan 1, 2001
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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