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- //! Eigenvalue decomposition for Hermite matrices
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+ //! Eigendecomposition for Hermitian matrices.
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+ //!
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+ //! For a Hermitian matrix `A`, this solves the eigenvalue problem `A V = V D`
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+ //! for `D` and `V`, where `D` is the diagonal matrix of eigenvalues in
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+ //! ascending order and `V` is the orthonormal matrix of corresponding
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+ //! eigenvectors.
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+ //!
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+ //! For a pair of Hermitian matrices `A` and `B` where `B` is also positive
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+ //! definite, this solves the generalized eigenvalue problem `A V = B V D`,
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+ //! where `D` is the diagonal matrix of generalized eigenvalues in ascending
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+ //! order and `V` is the matrix of corresponding generalized eigenvectors. The
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+ //! matrix `V` is normalized such that `V^H B V = I`.
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use ndarray:: * ;
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