02947nam 2200637 a 450 991045328100332120200520144314.01-281-82550-697866118255080-19-155139-2(CKB)1000000000556120(EBL)415082(OCoLC)276222156(SSID)ssj0000182939(PQKBManifestationID)11170879(PQKBTitleCode)TC0000182939(PQKBWorkID)10172313(PQKB)11725191(MiAaPQ)EBC415082(Au-PeEL)EBL415082(CaPaEBR)ebr10254375(CaONFJC)MIL182550(PPN)153970588(EXLCZ)99100000000055612020080128d2008 uy 0engur|n|---|||||txtccrAn introduction to stochastic filtering theory[electronic resource] /Jie XiongOxford ;New York Oxford University Press20081 online resource (285 p.)Oxford graduate texts in mathematics ;18Description based upon print version of record.0-19-921970-2 Includes bibliographical references (p. [255]-265) and index.Contents; 1 Introduction; 2 Brownian motion and martingales; 3 Stochastic integrals and Itô's formula; 4 Stochastic differential equations; 5 Filtering model and Kallianpur-Striebel formula; 6 Uniqueness of the solution for Zakai's equation; 7 Uniqueness of the solution for the filtering equation; 8 Numerical methods; 9 Linear filtering; 10 Stability of non-linear filtering; 11 Singular filtering; Bibliography; List of Notations; IndexStochastic filtering theory is a field that has seen a rapid development in recent years and this book, aimed at graduates and researchers in applied mathematics, provides an accessible introduction covering recent developments. - ;Stochastic Filtering Theory uses probability tools to estimate unobservable stochastic processes that arise in many applied fields including communication, target-tracking, and mathematical finance. As a topic, Stochastic Filtering Theory has progressed rapidly in recent years. For example, the (branching) particle system representation of the optimal filter has beeOxford graduate texts in mathematics ;18.Stochastic processesFilters (Mathematics)Prediction theoryElectronic books.Stochastic processes.Filters (Mathematics)Prediction theory.519.2/3Xiong Jie736517MiAaPQMiAaPQMiAaPQBOOK9910453281003321An introduction to stochastic filtering theory2231696UNINA