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# Calculate the eigenvectors and eigenvalues of the covariance matrix S. Each eigenvector has the same dimensionality ( number of components ) as the original images, and thus can itself be seen as an image.
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# and eigenvectors
# For each eigenvalue there are one or more corresponding eigenvectors ( which in this context are called eigenstates ), which will make up the state of the system after the measurement.
# There are no other positive ( moreover non-negative ) eigenvectors except positive multiples of v ( respectively, left eigenvectors except w ), i. e., all other eigenvectors must have at least one negative or non-real component.
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