New finite-dimensional risk-sensitive filters: small-noise limits

This paper is concerned with continuous-time nonlinear risk-sensitive filters. It is shown that for large classes of nonlinearities entering both the dynamics and measurements, these filters are finite-dimensional, generalizations of the Benes filters. Examples are given for rational and exponential nonlinearities. The small-noise limiting analog is discussed.

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