A note on sampling and parameter estimation in linear stochastic systems

doi:10.1109/9.802928

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A note on sampling and parameter estimation in linear stochastic systems

1999-01-01

DOI：10.1109/9.802928

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Abstract

En 中文

Numerical differentiation formulas that yield consistent least squares parameter estimates from sampled observations of linear, time invariant higher order systems have been introduced previously by Duncan et al. The formulas given by Duncan ct ai. have the same limiting system of equations as in the continuous time case. The formula presented in this note can be characterized as preserving asymptotically a partial integration rule. It leads to limiting equations for the parameter estimates that are different from the continuous case, but they again imply consistency. The numerical differentiation formulas given here can be used for an arbitrary linear system, which is not the ease in the previous paper by Duncan et al.

Keywords:

estimation

linear stochastic systems

numerical differentiation for stochastic systems

sampling

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