Similar to EFS, an SLP can be treated as a feature synthesizer, in which case the original audio features are propagated through the network and the output layer dimensionality is set equal to the total number of classes, L. We call the resulting output vector a class vector, as it indicates the class designated for a particular input FV.
Given an IF parametrised by f (t, Ψ), where Ψ is an M-dimensional parameter vector, a class of single component nonstationary signals can be defined as[30]: s ( t ) = a ( t ) e j 2 π ∫ − ∞ t f ( t, Ψ ) d τ (4).
For classification, the FE-RBM method computes the output for an input vector and a class vector by the negative free energy of an RBM.
where C is the number of classes, μ i is the mean vector of a class i, and M i is the number of samples within class i.
The SAFE analysis requires three input data structures: the gene expression data, a response vector, and a class matrix.
Classification is the module to classify the input feature vector into a class according to some rule, called a classifier.
Briefly, DWD projects data points onto the normal vector of a class (dataset) - separating hyperplane as calculated by a modified Support Vector Machine SVMM) and sub-tracts the class (dataset) means.
After extracting HE as feature vectors, a multi-class support vector machine (SVM) is trained to achieve a prediction model by using particle swarm optimization (PSO) to seek the optimal parameters of SVM, and then ten different bearing conditions are identified through the obtained SVM model.
Similar to an intensity vector, we therefore define a class label vector (2) where l i ∈?? is the class label of voxel i.
On the other hand, the strong vector equilibrium problem is a class of important equilibrium problems since a solution for the strong vector equilibrium problem is an ideal solution, which is better than other solutions such as efficient solution, weak efficient solution, Henig efficient solution and supper efficient solution (e.g., [36]).
