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The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets.
However, due to the statistical dependencies that potentially exist between the wavelet coefficients, the latter should not be selected independently from each other.
Note that the (hbox {dist}(A, B)) depends solely on the correlation between the wavelet coefficients in (A) and (B).
Accordingly, the above dissimilarity measure combines the absolute value of the correlation coefficient and the physical distance between the wavelet coefficients.
One way of achieving this is to apply complete linkage hierarchical clustering with the help of a dissimilarity measure that combines the time series temporal correlation and the physical distance between the wavelet coefficients.
Similar(55)
To overcome these shortcomings, a new simulation scheme, based on the Haar wavelet representation, is proposed in this study where the exact relation between the wind velocities and the wavelet coefficients is introduced.
The Kullback-Leibler distance (KLD) between the probability distribution of the wavelet coefficients of the reference and distorted images is used as a distortion measure.
The wavelet coefficients with wavelengths between 240 and 960 km were used to reconstruct the background Ne profile.
The wavelet coefficients statistical models which exploit the dependence between coefficients give better results compared to the ones using an independent assumption [5, 6, 8, 9].
Furthermore, as the relation between the wavelet domain coefficients and the measures of the quality of compression [root mean square error (RMSE) and local point error (LPE)] is not straightforward, it is difficult to achieve good control over the quality of compression by specifying thresholds on the wavelet coefficients.
The wavelet coefficients are stored as the feature vector.
More suggestions(15)
between the selection coefficients
between the partition coefficients
between the autocorrelation coefficients
between the balance coefficients
between the distribution coefficients
between the filtration coefficients
between the expansion coefficients
between the transport coefficients
between the sieving coefficients
between the polynomial coefficients
between the selectivity coefficients
between the fading coefficients
between the kappa coefficients
between the influence coefficients
between the entrainment coefficients
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