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Information Journal Paper

Title

Some new restart vectors for explicitly restarted Arnoldi method

Pages

  91-105

Abstract

 The Explicitly restarted Arnoldi method (ERAM) can be used to nd some eigenvalues of large and sparse matri-ces. However, it has been shown that even this method may fail to converge. In this paper, we present two new methods to accelerate the convergence of ERAM algo-rithm. In these methods, we apply two strategies for the updated initial vector in each restart cycles. The implementation of the methods have been tested by nu-merical examples. The results show that we can obtain a good acceleration of the convergence compared to orig-inal ERAM.

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    APA: Copy

    SHAHZADEH FAZELI, S.A., ABADI, Z., & KARBASSI, S.M.. (2019). Some new restart vectors for explicitly restarted Arnoldi method. JOURNAL OF ALGORITHMS AND COMPUTATION, 51(1), 91-105. SID. https://sid.ir/paper/354569/en

    Vancouver: Copy

    SHAHZADEH FAZELI S.A., ABADI Z., KARBASSI S.M.. Some new restart vectors for explicitly restarted Arnoldi method. JOURNAL OF ALGORITHMS AND COMPUTATION[Internet]. 2019;51(1):91-105. Available from: https://sid.ir/paper/354569/en

    IEEE: Copy

    S.A. SHAHZADEH FAZELI, Z. ABADI, and S.M. KARBASSI, “Some new restart vectors for explicitly restarted Arnoldi method,” JOURNAL OF ALGORITHMS AND COMPUTATION, vol. 51, no. 1, pp. 91–105, 2019, [Online]. Available: https://sid.ir/paper/354569/en

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