Interacting Particle Filtering With Discrete Observations

  • Pierre Del Moral
  • Jean Jacod
Part of the Statistics for Engineering and Information Science book series (ISS)


We consider a pair of processes (X,Y), where X represents the state of a system (or signal) and Y represents the observation: X may take its values in an arbitrary measurable space (E,ε), but it is important for what follows that Y take its values in q for some q ≥ 1.


Transition Kernel Gaussian Variable Interact Particle System Total Variation Distance Discrete Observation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 2001

Authors and Affiliations

  • Pierre Del Moral
  • Jean Jacod

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