Interacting Particle Filtering With Discrete Observations
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 ℝ q for some q ≥ 1.
KeywordsTransition Kernel Gaussian Variable Interact Particle System Total Variation Distance Discrete Observation
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