Stochastic Processes and Filtering Theory
(eBook)

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Published
Dover Publications, 2013.
Status
Available Online

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Format
eBook
Language
English
ISBN
9780486318196

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Citations

APA Citation, 7th Edition (style guide)

Andrew H. Jazwinski., & Andrew H. Jazwinski|AUTHOR. (2013). Stochastic Processes and Filtering Theory . Dover Publications.

Chicago / Turabian - Author Date Citation, 17th Edition (style guide)

Andrew H. Jazwinski and Andrew H. Jazwinski|AUTHOR. 2013. Stochastic Processes and Filtering Theory. Dover Publications.

Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)

Andrew H. Jazwinski and Andrew H. Jazwinski|AUTHOR. Stochastic Processes and Filtering Theory Dover Publications, 2013.

MLA Citation, 9th Edition (style guide)

Andrew H. Jazwinski, and Andrew H. Jazwinski|AUTHOR. Stochastic Processes and Filtering Theory Dover Publications, 2013.

Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.

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Grouped Work ID301c6f93-86ba-2cef-ecc5-f63903c9943e-eng
Full titlestochastic processes and filtering theory
Authorjazwinski andrew h
Grouping Categorybook
Last Update2023-10-07 20:16:12PM
Last Indexed2024-04-18 00:01:20AM

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First LoadedJul 20, 2023
Last UsedFeb 4, 2024

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    [synopsis] => This unified treatment of linear and nonlinear filtering theory presents material previously available only in journals, and in terms accessible to engineering students. Its sole prerequisites are advanced calculus, the theory of ordinary differential equations, and matrix analysis. Although theory is emphasized, the text discusses numerous practical applications as well. Taking the state-space approach to filtering, this text models dynamical systems by finite-dimensional Markov processes, outputs of stochastic difference, and differential equations. Starting with background material on probability theory and stochastic processes, the author introduces and defines the problems of filtering, prediction, and smoothing. He presents the mathematical solutions to nonlinear filtering problems, and he specializes the nonlinear theory to linear problems. The final chapters deal with applications, addressing the development of approximate nonlinear filters, and presenting a critical analysis of their performance.
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