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We suggested a novel equation for interval distance of interval numbers which can be utilized to form normalization technique for interval target-based decision making problems.
Feature moment normalization techniques normalize the statistical moments of speech features.
In a transformation-based approach, the scores are usually normalized to a common domain by one of several normalization techniques (e.g., z-normalization [38], F-normalization [39], and EER-normalization [40]) and the normalized scores are then combined.
Normalization techniques aim to correct such biases.
Image normalization techniques included both automatic scattergram-controlled regression (ASCR) and localized relative radiometric normalization (LRRN) techniques.
Shippy, R. et al. Using rna sample titrations to assess microarray platform performance and normalization techniques.
The formulation and normalization techniques are illustrated with two example cases.
Standard normalization techniques fail to correct for these hidden variables and lead to flawed downstream analyses.
Moreover, the processing is fast when compared to the existing illumination normalization techniques.
Finally, NMDF and VMD are normalization techniques.
Cepstral mean normalization (CMN) [10] is one of the most popular feature moment normalization techniques.
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