2021
DOI: 10.3390/math9172018
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An Improved Taylor Algorithm for Computing the Matrix Logarithm

Abstract: The most popular method for computing the matrix logarithm is a combination of the inverse scaling and squaring method in conjunction with a Padé approximation, sometimes accompanied by the Schur decomposition. In this work, we present a Taylor series algorithm, based on the free-transformation approach of the inverse scaling and squaring technique, that uses recent matrix polynomial formulas for evaluating the Taylor approximation of the matrix logarithm more efficiently than the Paterson–Stockmeyer method. T… Show more

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Cited by 4 publications
(4 citation statements)
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References 45 publications
(71 reference statements)
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“…The MATLAB Symbolic Math Toolbox with 256 digits of precision was employed to compute "exactly" the matrix logarithm function using the vpa (variable-precision floating-point arithmetic) function. The battery featured the following three matrix sets, which are practically the same as the ones used and described in [44]:…”
Section: Numerical Testsmentioning
confidence: 99%
See 2 more Smart Citations
“…The MATLAB Symbolic Math Toolbox with 256 digits of precision was employed to compute "exactly" the matrix logarithm function using the vpa (variable-precision floating-point arithmetic) function. The battery featured the following three matrix sets, which are practically the same as the ones used and described in [44]:…”
Section: Numerical Testsmentioning
confidence: 99%
“…The size of these was 128 × 128. The matrix logarithm of each matrix was computed "exactly" according to this protocol, as described in [44]:…”
Section: Numerical Testsmentioning
confidence: 99%
See 1 more Smart Citation
“…Computation methods for the principal value of the matrix logarithm can be found in several articles using different approaches. In [3], an improvement of the inverse scaling and squaring method is shown; in [4], an alternative formulation of the matrix arithmeticgeometric mean algorithm is used; in [5], multiprecision algorithms are analyzed; in [6], algorithms based on a numerical spectral decomposition or on a numerical Jordan decomposition are used; in [7], algorithms based on the double exponential formula are used; and in [8], an improved Taylor algorithm is applied. However, the closest example to our approach is the paper by N. Hale, N.J. Higham, N.J. and L.N.…”
Section: Introductionmentioning
confidence: 99%