An Introduction to Stochastic Filtering Theory (Oxford Graduate Texts in Mathematics, #18) (Oxford Graduate Texts in Mathematics; Oxford Mathematics)

by Jie Xiong

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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 been extensively studied to seek more effective numerical approximations of the optimal filter; the stability of the filter with "incorrect" initial state, as well as the long-term behavior of the optimal filter, has attracted the attention of many researchers; and although still in its infancy, the study of singular filtering
models has yielded exciting results.

In this text, Jie Xiong introduces the reader to the basics of Stochastic Filtering Theory before covering these key recent advances. The text is written in a style suitable for graduates in mathematics and engineering with a background in basic probability.
  • ISBN10 0199219702
  • ISBN13 9780199219704
  • Publish Date 17 April 2008 (first published 1 January 2008)
  • Publish Status Active
  • Publish Country GB
  • Imprint Oxford University Press
  • Format Hardcover
  • Pages 286
  • Language English