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Set-membership techniques for estimating parameters from uncertain data are reviewed. Contrary to the prevailing usage, the error in the data is not considered as a random variable with known or… (More)

A method is described which exactly characterizes the set of all the values of the parameter vector of a linear model that are consistent with bounded errors on the measurements. It provides a… (More)

Bounded-error estimation aims at characterizing the set of all parameter vectors consistent with given data and prior bounds on acceptable values for the errors. In this paper, two recursive… (More)

An important problem arising when one wants to estimate the parameters of a model in a bounded-error context is the specification of reliable bounds for this error. In early phases of development,… (More)

- Eric Walter, Héléne Piet-Lahanier
- 26th IEEE Conference on Decision and Control
- 1987

A method is described to exactly characterize the set of all the values of the parameter vector of a linear model that are coherent with bounded errors on the measurements. It provides a… (More)

When the error between the data and the corresponding model output is affine in the parameters to be estimated, the set § of all values of the parameter vector that are feasible (in the sense that… (More)

- Eric Walter, Héléne Piet-Lahanier
- 25th IEEE Conference on Decision and Control
- 1986

When modeling a system, it is of importance to assess the uncertainty on the estimated values of the parameters. This is usually done by taking advantage of the asymptotic properties of maximum… (More)

- Héléne Piet-Lahanier, E Trzcienski Walter
- Proceedings of the 28th IEEE Conference on…
- 1989

When the (prediction) error is only known to be bounded, it is interesting to characterize the set of all values of the parameters to be estimated that are consistent with the data, error bounds, and… (More)

- Luc Pronzato, E Trzcienski Walter, Héléne Piet-Lahanier
- Proceedings of the 28th IEEE Conference on…
- 1989

Bounded-error estimation aims at characterizing the set of all parameter vectors consistent with prior bounds on the errors between the measurements and model outputs. E. Fogel and Y.F. Huang… (More)

Set-membership estimation (or parameter bounding) assumes that the error corrupting the data is described only by upper and lower bounds between which its realizations must lie. It aims at providing… (More)