Abstract.
Deterministic filter models are considered, and a criterion for a deterministic filter to be robust is introduced. Among the candidates for robust deterministic filters are so-called minimax estimators. In the second part of the paper, a risk sensitive stochastic approach to nonlinear filtering is considered, in which the traditional expected mean squared error criterion is replaced by an expected exponential-of-mean squared error. Minimax filters are obtained as totally risk averse limits of risk sensitive filters.
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Date received: July 22, 1999. Date revised: June 19, 2000.
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Fleming, W., McEneaney, W. Robust Limits of Risk Sensitive Nonlinear Filters. Math. Control Signals Systems 14, 109–142 (2001). https://doi.org/10.1007/PL00009879
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DOI: https://doi.org/10.1007/PL00009879