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5.2 Pattern association algorithm

The training data are $ \bf x_{i}^{}$ $ \in$ IRd with i = 1,..., n. In training, the kernel matrix $ \bf\tilde{\bf K}$, its eigenvectors $ \bf a^{l}_{}$ (section 2.4), and (if used) the reduced set {$ \bf y_{i}^{}$,$ \beta_{i}^{l}$} (appendix B.2) are computed. From these values, the potential E of a point $ \bf z$ $ \in$ IRd can be obtained. In recall, a pattern is completed by a gradient descent in the potential field E($ \bf z$).


Heiko Hoffmann