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Calculation of the feature is quite complex.
Calculation of the feature vectors including 12 cepstral and a log-energy parameter and their first and second order dynamic parameters.
h) Calculation of the logarithms of mel-frequency filter bank outputs (i) Application of DCT to the sequence resulting from previous step (j) Calculation of the feature vectors including 12 cepstral and a log-energy parameter and their first and second order dynamic parameters .
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The recurrent calculation of the features is performed without any further processing step-like outlier removal or feature sectioning.
The processing times for classification (including calculation of the features) and regularization were recorded on a Intel® Core™ 2 CPU (Q6600), running at 2.4 GHz and containing 4 GB of memory.
The first step calculates a feature set that represents each residue in the input sequence using a sliding window, i.e. the calculation of the features is based on a segment of residues centered over the input (to-be-predicted) residue.
The calculation of this feature can be more or less complex.
The calculation time of the feature list cross-correlation algorithms only depends on the length of the feature-lists.
Calculations of the features for each position in the window was inspired by the previous methods, α-MoRF-PredI and α-MoRF-PredII, which used predicted disorder and secondary structure.
The calculation of this features considers a forgetting function (or cooling function) to reinforce the latest acquired information.
The equation above is useful for calculation of the RMS features of all channels.
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