Computing the Inverse Matrix Hyperbolic Sine
NAA '00 Revised Papers from the Second International Conference on Numerical Analysis and Its Applications
Computing estimates of continuous time macroeconometric models on the basis of discrete data
Computational Statistics & Data Analysis
A New Scaling and Squaring Algorithm for the Matrix Exponential
SIAM Journal on Matrix Analysis and Applications
Configuration products and quotients in geometric modeling
Computer-Aided Design
A more accurate Briggs method for the logarithm
Numerical Algorithms
Tradeoffs in linear time-varying systems: an analogue of Bode's sensitivity integral
Automatica (Journal of IFAC)
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The Schur--Fréchet method of evaluating matrix functions consists of putting the matrix in upper triangular form, computing the scalar function values along the main diagonal, and then using the Fréchet derivative of the function to evaluate the upper diagonals. This approach requires a reliable method of computing the Fréchet derivative. For the logarithm this can be done by using repeated square roots and a hyperbolic tangent form of the logarithmic Fréchet derivative. Padé approximations of the hyperbolic tangent lead to a Schur--Fréchet algorithm for the logarithm that avoids problems associated with the standard "inverse scaling and squaring" method. Inverting the order of evaluation in the logarithmic Fréchet derivative gives a method of evaluating the derivative of the exponential. The resulting Schur--Fréchet algorithm for the exponential gives superior results compared to standard methods on a set of test problems from the literature.