Abstract
A procedure for finding the eigenvectors and eigenvalues of a real symmetric matrix, dubbed the ‘JK method,’ is presented. It is similar to Jacobi's classic procedure, but involves only a post-multiplying orthonormal transformation. When both eigenvectors and eigenvalues are wanted, the JK method has advantages, both in computational time and in storage requirements, over Jacobi's procedure.

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