Comparison of three Frisch methods for errors-in-variables identification

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Comparison of three Frisch methods for errors-in-variables identification

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 dynamic errors–in– variables models. One of the more promising approaches is the so–called Frisch scheme. This report decribes three different estimation criteria within the Frisch context and compares...

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Extending the Frisch scheme for errors-in-variables identification to correlated output noise

Several estimation methods have been proposed for identifying errors-invariables systems, where both input and output measurements are corrupted by noise. One of the promising approaches is the so called Frisch scheme. In its standard form it is designed to handle white measurement noise on the input and output sides. As the output noise comprises both effects of measurement errors and of proce...

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ژورنال

عنوان ژورنال: IFAC Proceedings Volumes

سال: 2008

ISSN: 1474-6670

DOI: 10.3182/20080706-5-kr-1001.00070