LEADER 00000cam a2200649Ma 4500 
001    ocn276222156 
003    OCoLC 
005    20160527041246.7 
006    m     o  d         
007    cr zn||||||||| 
008    080128s2008    enk     ob    001 0 eng d 
019    294901997|a308670970|a437092644|a646766995 
020    0191551392|q(electronic book) 
020    9780199219704 
020    0199219702 
020    9780191551390|q(ebook) 
020    0191551392|q(ebook) 
020    |z0199219702|q(Cloth) 
035    (OCoLC)276222156|z(OCoLC)294901997|z(OCoLC)308670970
       |z(OCoLC)437092644|z(OCoLC)646766995 
040    CDX|beng|epn|cCDX|dOCLCQ|dOSU|dN$T|dYDXCP|dIDEBK|dE7B
       |dOCLCQ|dEBLCP|dOCLCO|dOCLCQ|dOCLCF|dOCLCQ|dDEBSZ|dOCLCQ
       |dMERUC 
049    RIDW 
050  4 QA274|b.X56 2008eb 
072  7 MAT|x029040|2bisacsh 
082 04 519.2/3 22|222 
090    QA274|b.X56 2008eb 
100 1  Xiong, Jie.|0https://id.loc.gov/authorities/names/
       n96040053 
245 13 An introduction to stochastic filtering theory /|cJie 
       Xiong. 
264  1 Oxford, UK :|bOxford University Press,|c2008. 
300    1 online resource (xiii, 270 pages). 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
347    text file|2rdaft 
490 1  Oxford graduate texts in mathematics ;|v18 
490 1  Oxford mathematics 
504    Includes bibliographical references and index. 
505 0  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; 
       Index. 
520    Stochastic 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 bee. 
588 0  Print version record. 
590    eBooks on EBSCOhost|bEBSCO eBook Subscription Academic 
       Collection - North America 
650  0 Stochastic processes.|0https://id.loc.gov/authorities/
       subjects/sh85128181 
650  0 Filters (Mathematics)|0https://id.loc.gov/authorities/
       subjects/sh85048251 
650  0 Prediction theory.|0https://id.loc.gov/authorities/
       subjects/sh85106258 
650  7 Stochastic processes.|2fast|0https://id.worldcat.org/fast/
       1133519 
650  7 Filters (Mathematics)|2fast|0https://id.worldcat.org/fast/
       924327 
650  7 Prediction theory.|2fast|0https://id.worldcat.org/fast/
       1075037 
655  4 Electronic books. 
776 08 |iPrint version:|aXiong, Jie.|tIntroduction to stochastic 
       filtering theory.|dOxford, UK : Oxford University Press, 
       2008|w(DLC)  2008004176 
830  0 Oxford graduate texts in mathematics ;|0https://id.loc.gov
       /authorities/names/n96121759|v18. 
830  0 Oxford mathematics.|0https://id.loc.gov/authorities/names/
       no2006130077 
856 40 |uhttps://rider.idm.oclc.org/login?url=http://
       search.ebscohost.com/login.aspx?direct=true&scope=site&
       db=nlebk&AN=259511|zOnline eBook. Access restricted to 
       current Rider University students, faculty, and staff. 
856 42 |3Instructions for reading/downloading this eBook|uhttp://
       guides.rider.edu/ebooks/ebsco 
901    MARCIVE 20231220 
948    |d201606016|cEBSCO|tebscoebooksacademic|lridw 
994    92|bRID