A Gaussian classifier, which classifies an input vector as belonging to one of the gaussian distributions defined in a specially-formatted Buffer.
The Buffer should be single-channel. Its exact format is specified towards the bottom of this file. If you have the MathLib quark installed then you can use the convenience function GaussClass.classesToFloatArray() to create a FloatArray suitable for loading to a Buffer.
input signal, a multichannel signal specifying a co-ordinate in the space (i.e. a vector).
the buffer in which the shapes and weights of the gaussian components are specified.
the classifier is only active when this is greater than 0 (otherwise, previous value is held constant). Its default value is 1.
The following example creates two-dimensional data with three classes:
THE FORMAT OF THE BUFFER:
The Buffer should be single-channel and hold data in the following order, once for each class:
- N floats: the mean vector;
- N*N floats: the inverse of the covariance matrix; and
- 1 float: the weight of the component divided by the square root of the determinant of the covariance matrix.
N is the dimensionality of the data space. The length of the Buffer is therefore C * (N*N + N + 1). GaussClass.kr will determine the number of classes from the size of the Buffer.