Abstract
Many different problems such as linear and nonlinear regressions, parameter and state estimation of dynamic systems, state space and time series prediction, interpolation, smoothing, function approximation have a common general structure that here is referred to as generalized estimation problem. In all these problems one has to evaluate some unknown variable using available data (often obtained by measurements on a real process). Available data are always associated with some uncertainty and it is necessary to evaluate how this uncertainty affects the estimated variables.
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© 1989 Plenum Press, New York
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Milanese, M. (1989). Estimation and Prediction in the Presence of Unknown but Bounded Uncertainty: A Survey. In: Milanese, M., Tempo, R., Vicino, A. (eds) Robustness in Identification and Control. Applied Information Technology. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-9552-6_1
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