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The basis functions are typically found by computing the [[eigenvector]]s of the [[covariance matrix]] of the data set. This is the same as performing [[principal components analysis]] on the data. A more advanced technique is to form a [[kernel matrix]] out of the data, using a fixed [[kernel (mathematics)|kernel]]. The basis functions from the eigenvectors of the kernel matrix are thus non-linear in the ___location of the data (see [[Mercer's theorem]] and the [[kernel trick]] for more information).
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*[[Source separation]]
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