Inverse eigenvalues theorem: Difference between revisions

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Line 1: #REDIRECT [[Eigendecomposition of a matrix]] In [[numerical analysis]] and [[linear algebra]], this theorem states that <math>\lambda</math> is an [[eigenvalue]] of <math>A</math> if and only if <math>\lambda^{-1}</math> is an eigenvalue of <math>A^{-1}</math>.