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Applications

  • R. S. Bucy
Part of the Signal Processing and Digital Filtering book series (SIGNAL PROCESS)

Abstract

Recall from the previous lecture that the conditional density is given by
$${P^{{x_n}|{z_o} \ldots {z_n}}}\left( \xi \right) \triangleq {F_n}\left( \xi \right) = \frac{{{D_n}\left( \xi \right){P_n}\left( \xi \right)}}{{{N_n}}},$$
Where Dn is
$${D_n}\left( \xi \right) = {v_n}\left( {{z_n} - h\left( \xi \right)} \right),$$
ν n is the density of the nth observation noise, and
$${N_n} = \int { \cdots \int {{D_n}} } \left( \xi \right){f_n}\left( \xi \right)d\xi $$
is the normalizing factor.

Keywords

Riccati Equation Sensor Orbit Nonlinear Filter Nonlinear Stochastic System Sensor Problem 
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-Verlag New York, Inc. 1994

Authors and Affiliations

  • R. S. Bucy
    • 1
  1. 1.Department of Aerospace EngineeringUniversity of Southern CaliforniaLos AngelesUSA

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