Often the easiest way to discretize an ordinary or partial differential equation is by a rectangular numerical method, in which n basis functions are sampled at m>>n collocation points. We show how eigenvalue problems can be solved in this setting by QR reduction to square matrix generalized eigenvalue problems. The method applies equally in the limit "m=infinity" of eigenvalue problems for quasimatrices. Numerical examples are presented as well as pointers to some related literature.

翻译：通常,将普通或部分差异方程分解的最简单方法是采用矩形数字法,在m ⁇ n合用点取样n基函数。我们展示了如何通过将QR减到平方矩阵的普遍电子值问题来解决在此环境中的二元值问题。该方法同样适用于准分子的“m=infinity”的二次值问题。数字示例以及一些相关文献的指针。