East Asian J. Appl. Math., 7 (2017), pp. 799-809.
Published online: 2018-02
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We propose a robust numerical algorithm for solving the nonlinear eigenvalue problem $A(λ)x=0$. Our algorithm is based on the idea of finding the value of $λ$ for which $A(λ)$ is singular by computing the smallest eigenvalue or singular value of $A(λ)$ viewed as a constant matrix. To further enhance computational efficiency, we introduce and use the concept of signed singular value. Our method is applicable when $A(λ)$ is large and nonsymmetric and has strong nonlinearity. Numerical experiments on a nonlinear eigenvalue problem arising in the computation of scaling exponent in turbulent flow show robustness and effectiveness of our method.
}, issn = {2079-7370}, doi = {https://doi.org/10.4208/eajam.181016.300517c}, url = {http://global-sci.org/intro/article_detail/eajam/10721.html} }We propose a robust numerical algorithm for solving the nonlinear eigenvalue problem $A(λ)x=0$. Our algorithm is based on the idea of finding the value of $λ$ for which $A(λ)$ is singular by computing the smallest eigenvalue or singular value of $A(λ)$ viewed as a constant matrix. To further enhance computational efficiency, we introduce and use the concept of signed singular value. Our method is applicable when $A(λ)$ is large and nonsymmetric and has strong nonlinearity. Numerical experiments on a nonlinear eigenvalue problem arising in the computation of scaling exponent in turbulent flow show robustness and effectiveness of our method.