Properties of risk-sensitive filters/estimators

Algorithms for risk-sensitive filters have been developed in literature and connections to H_∞ filtering also established. The risk-sensitive filter differs from a conditional mean estimator (Kalman filter) and is either risk-prone or risk-averse depending on the sign of a scalar θ that appears in the cost function. The RS filter exhibits many interesting properties. Statistical properties, parameter estimation and explicit bounds of estimation for these filters are presented in the paper