Abstract
The algorithm is based on an exact relation, due to Cooley, Lewis and Welch, between the Discrete Fourier Transform and the periodic sums, associated with a function and its Fourier Transform in a similar way as in the Poisson summation formula. It makes use of several equidistant grids, with the same number of points covering m different symmetric intervals of length L, 2L, 4L, 8L,…, where it applies FFT and spline interpolation to the midpoints of the grid.
Typically the number of arithmetic operations per computed function value is about twice as large as for the FFT, but the distribution of points is more adequate for many applications, because the union of the grids is, globally, an approximately equidistant grid on a logarithmic scale. Some properties and applications of the algorithm will be discussed.
Novel features emphasized in this article include a new initial condition, where there is some relation to the work of Walter Gautschi on Practical Fourier Analysis, and the use of convolution smoothing to improve the performance on problems with discontinuities in the time domain.
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Dedicated to Walter Gautschi on the occasion of his 65th birthday
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© 1994 Birkhäuser
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Dahlquist, G. (1994). A Multigrid FFT Algorithm for Slowly Convergent Inverse Laplace Transforms. In: Zahar, R.V.M. (eds) Approximation and Computation: A Festschrift in Honor of Walter Gautschi. ISNM International Series of Numerical Mathematics, vol 119. Birkhäuser, Boston, MA. https://doi.org/10.1007/978-1-4684-7415-2_9
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DOI: https://doi.org/10.1007/978-1-4684-7415-2_9
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