A Finitely Additive White Noise Approach to Nonlinear Filtering.
NORTH CAROLINA UNIV AT CHAPEL HILL DEPT OF STATISTICS
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A finitely additive white noise approach to nonlinear filtering is developed. It is shown that a pathwise solution of the problem is possible where the observed paths belong to the reproducing kernel Hilbert space of the Wiener process. Connections with robust filtering and recent developments are explored. Author
- Statistics and Probability