Comparison of three Frisch methods for errors-in-variables identification
作者： Mei Hong , Torsten Söderström , Umberto Soverini , Roberto Diversi
DOI: 10.3182/20080706-5-KR-1001.00070
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摘要: Abstract The errors–in–variables framework concerns static or dynamic systems whose input and output variables are affected by additive noise. Several estimation methods have been proposed for identifying models. One of the more promising approaches is so–called Frisch scheme. This paper decribes three different criteria within context compares their accuracy on basis asymptotic covariance matrices estimates. Some numerical examples support well theoretical results.
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