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The L2 error with integration with respect to the design measure is used as error criterion.
It is shown that under a mean square error criterion, a natural convex geometry arises.
Finally, the fine time adjustment based on the minimum mean-squared error criterion is performed.
The fuzzy controller is optimized using a least squares error criterion.
Moreover, the error criterion with respect to optimization and measurement is different.
The following test used the relative error criterion, though at certain points the relative error could be much higher than indicated.
The error criterion was relative when the function magnitude was greater than one but absolute when it was less than one.
Both the frequency-domain channel estimation and equalization are designed by the linear minimum mean square error criterion.
The approach followed in the present proposes to use an ITSE (Integral of the Time-weighted Square Error) criterion.
A novel robust estimator using correntropy, an information theoretic alternative to the traditional mean square error criterion, is proposed.
The L2 error with integration with respect to the design measure is used as an error criterion.
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