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pro vyhledávání: '"Tsu T. Soong"'
Autor:
Peter A. Ruymgaart, Tsu T. Soong
The second edition has not deviated significantly from the first. The printing of this edition, however, has allowed us to make a number of corrections which escaped our scrutiny at the time of the first printing, and to generally improve and tighten
Autor:
P.A. Ruymgaart, Tsu T. Soong
Since their introduction in the mid 1950s, the filtering techniques developed by Kalman, and by Kalman and Bucy have been widely known and widely used in all areas of applied sciences. Starting with applications in aerospace engineering, their impact
Autor:
Tsu T. Soong, Peter A. Ruymgaart
Publikováno v:
Mathematics of Kalman-Bucy Filtering ISBN: 9783540187813
Mathematics of Kalman-Bucy Filtering ISBN: 9783642968440
Mathematics of Kalman-Bucy Filtering ISBN: 9783642968440
In the design and analysis of a physical dynamic system, filtering refers to the estimation of the system state on the basis of system measurements contaminated by random noise. The Kalman-Bucy filter, being an algorithm for computing estimates of th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0e54dbfc1097b919b7e5714dc4770d79
https://doi.org/10.1007/978-3-642-73341-3_3
https://doi.org/10.1007/978-3-642-73341-3_3
Autor:
Peter A. Ruymgaart, Tsu T. Soong
Publikováno v:
Springer Series in Information Sciences ISBN: 9783642968440
Springer Series in Information Sciences ISBN: 9783540187813
Springer Series in Information Sciences ISBN: 9783540187813
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b47f0ef25c742376ca0b81ed6d03abce
https://doi.org/10.1007/978-3-642-96842-6
https://doi.org/10.1007/978-3-642-96842-6
Autor:
Tsu T. Soong, Peter A. Ruymgaart
Publikováno v:
Mathematics of Kalman-Bucy Filtering ISBN: 9783540187813
Mathematics of Kalman-Bucy Filtering ISBN: 9783642968440
Mathematics of Kalman-Bucy Filtering ISBN: 9783642968440
As the Kalman-Bucy filtering theory is a probabilistic concept, an understanding of some basic concepts in probability theory is necessary in the study of this subject. We begin this discourse by reviewing some of the basic elements in probability th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8f14d5bb4bbb8f245649ad449fd696eb
https://doi.org/10.1007/978-3-642-73341-3_1
https://doi.org/10.1007/978-3-642-73341-3_1
Autor:
Tsu T. Soong, Peter A. Ruymgaart
Publikováno v:
Mathematics of Kalman-Bucy Filtering ISBN: 9783540187813
Mathematics of Kalman-Bucy Filtering ISBN: 9783642968440
Mathematics of Kalman-Bucy Filtering ISBN: 9783642968440
Having introduced the concept of a stochastic process in Sect. 1.4, some elements of calculus in mean square, or m.s. calculus, are discussed in this chapter to the extent required for Chap. 3. Since the class of stochastic processes to be considered
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a28f0c89194cdbabd8678b80fb69cf59
https://doi.org/10.1007/978-3-642-73341-3_2
https://doi.org/10.1007/978-3-642-73341-3_2
Autor:
Tsu T. Soong, Peter A. Ruymgaart
Publikováno v:
Mathematics of Kalman-Bucy Filtering ISBN: 9783642968440
Mathematics of Kalman-Bucy Filtering ISBN: 9783540187813
Mathematics of Kalman-Bucy Filtering ISBN: 9783540187813
A relatively complete mathematical development of the Kalman-Bucy filter has been presented in Chap. 4. One of the results that emerged in this discourse is the fact that success of the filter depends on the contamination of observation by white nois
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a87998daebf3a14a6154d3abd1285af2
https://doi.org/10.1007/978-3-642-96842-6_5
https://doi.org/10.1007/978-3-642-96842-6_5
Autor:
Peter A. Ruymgaart, Tsu T. Soong
Publikováno v:
Mathematics of Kalman-Bucy Filtering ISBN: 9783540187813
Mathematics of Kalman-Bucy Filtering ISBN: 9783642968440
Mathematics of Kalman-Bucy Filtering ISBN: 9783642968440
Equation (3.1 or 3) mathematically describes the dynamic model in the Kalman-Bucy filter, whose output is a stochastic vector process to be estimated on the basis of noise-contaminated observations. To complete the Kalman-Bucy model for the estimatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::465f60a261ca7f2eb31c1af9b366076c
https://doi.org/10.1007/978-3-642-73341-3_4
https://doi.org/10.1007/978-3-642-73341-3_4
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