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Exact(17)
The parameters c A and c B are the mean values of the feature f in classes A and B, respectively.
In the case of a genuine MP3 track, all the values of the feature will be similar, so that the EM algorithm will usually find a single cluster.
Conversely, in the presence of tampering, the segments corresponding to the manipulated part will have different values of the feature with respect to the original part.
where x n and q n are the n th-dimensional values of the feature vectors of tracks X and Q, respectively.
To explain the algorithm, we assume that there are only two classes so it forms a binary classification problem and that the values of the feature belong to a finite sample space.
where μ L and μ R are the mean values of the feature over all trials for classes L and R, respectively, and (σ L )2 and (σ R )2 are the trial-wise variances of the feature.
Similar(43)
In these networks the input layer is a standard framewise cepstral representation, and the output layer represents the values of the features.
The columns represent the measured values of the features.
Figure 3 Values of the features for different postures.
Few other techniques use the numerical values of the features coupled to statistical classification methods.
The impact of the choice of different local optima size over the values of the features is depicted in Figure 14.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com