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Hardware architectures for eigenvalue computation of real symmetric matrices

Hardware architectures for eigenvalue computation of real symmetric matrices

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Computation of eigenvalues is essential in many applications in the fields of science and engineering. When the application of interest requires the computation of eigenvalues of high throughput or real-time performance, a hardware implementation of an eigenvalue computation block is often employed. The problem of eigenvalue computation of real symmetric matrices is focused upon. For the general case of a symmetric matrix eigenvalue problem, the approximate Jacobi method is proposed, where for the special case of a 3×3 symmetric matrix, an algebraic-based method is introduced. The proposed methods are compared with various other approaches reported in the literature. Results obtained by mapping the above architectures on a field programmble gate array device illustrate the advantages of the proposed methods over the existing ones.

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