Marsyas
0.6.0-alpha
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Principal Component Analysis. More...
#include <PCA.h>
Inherits MarSystem.
Public Member Functions | |
MarSystem * | clone () const |
void | myProcess (realvec &in, realvec &out) |
Processes data. | |
PCA (std::string name) | |
PCA (const PCA &a) | |
void | tqli (mrs_real d[], mrs_real e[], mrs_natural m, realvec &z) |
void | tred2 (realvec &a, mrs_natural m, mrs_real *d, mrs_real *e) |
~PCA () |
Principal Component Analysis.
Perform Principal Component Analysis (PCA) on all samples of the incoming realvec of data. The correlation method is taken, with a correlation matrix computed over all samples within the single input realvec. Eigenvalue/Eigenvector calculation is by the QL algorithm (ie. not suitable when the correlation matrix is singular or near singular). Output is the set of input samples projected onto the top "npc" (a MarSystem control) principal components.
void tqli | ( | mrs_real | d[], |
mrs_real | e[], | ||
mrs_natural | m, | ||
realvec & | z | ||
) |
void tred2 | ( | realvec & | a, |
mrs_natural | m, | ||
mrs_real * | d, | ||
mrs_real * | e | ||
) |