We present a new approach to compute selected eigenvalues and eigenvectors of the two-parameter eigenvalue problem. Our method requires computing generalized eigenvalue problems of the same size as the matrices of the initial two-parameter eigenvalue problem. The method is applicable for  a class of Helmholtz equations when separation of variables is applied  .
We present a new approach to compute selected eigenvalues and eigenvectors of the two-parameter eigenvalue problem. Our method requires computing generalized eigenvalue problems of the same size as the matrices of the initial two-parameter eigenvalue problem. The method is applicable for right definite problems, possibly after performing an affine transformation. This includes a class of Helmholtz equations when separation of variables is applied . We provide a convergence proof for extremal eigenvalues and empirical evidence along with a local convergence proof for other eigenvalues .
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right definite problems, possibly after performing an affine transformation. This includes
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. We provide a convergence proof for extremal eigenvalues and empirical evidence along with a local convergence proof for other eigenvalues