An Introduction to Stochastic Filtering Theory

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An Introduction to Stochastic Filtering Theory (Oxford Graduate Texts in Mathematics)
Oxford University Press | English | 2008-09-15 | ISBN: 0199219702 | 224 pages | PDF | 15 MB

Stochastic Filtering Theory uses presumption tools to estimate unobservable stochastic processes that arise in many applied fields including commerce, target-tracking, and mathematical finance. As a topi>c, Stochastic Filtering Theory has progressed expeditiously in recent years. For example, the (branching) particle system representation of the optimal strain has been extensively studied to seek more effective numerical approximations of the optimal pass through a strainer; the stability of the filter with incorrect initial state, as well during the time that the long-term behavior of the optimal filter, has attracted the watchfulness of many researchers; and although still in its infancy, the study of unique filtering models has yielded exciting results.
In this text, Jie Xiong introduces the reader to the basics of Stochastic Filtering Theory in the presence of covering these key recent advances. The text is written in a fashion suitable for graduates in mathematics and engineering with a background in basic probability.

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