Functions which can be represented by rapidly converging Walsh-series play an important role in the theory of signal-processing and image-processing. A special Quasi-Monte Carlo method for the numerical integration of such functions in high dimensions is developed in the present paper. The method is
Quasi-Monte Carlo methods for the numerical integration of multivariate walsh series
β Scribed by G. Larcher; W.Ch. Schmid; R. Wolf
- Publisher
- Elsevier Science
- Year
- 1996
- Tongue
- English
- Weight
- 781 KB
- Volume
- 23
- Category
- Article
- ISSN
- 0895-7177
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β¦ Synopsis
In
[l], a method for the numerical integration of multivariate Walsh series, based on low-discrepancy point sets, was developed. In the present paper, we improve and generalize error estimates given in [l] and disprove a conjecture stated in [1,2]. Keywords-Numerical integration, Walsh series, Low-discrepancy point sets, Quasi-Monte Carlo methods. RN(f) := 1)' f(x) dx -$ N2 f(x,) n=O < K(s, a, c, b) . bt("-') . "";f~:-l, for all f E JZz (c) .
π SIMILAR VOLUMES
An essentially best possible estimate for the order of magnitude of the integration error occurring by numerically integrating multivariate Walsh series in a prime power base b by means of digital (t, m, s)-nets constructed over the finite field β«ήβ¬ b is given.
The Laplace transform is applied to remove the time-dependent variable in the di usion equation. For nonharmonic initial conditions this gives rise to a non-homogeneous modiΓΏed Helmholtz equation which we solve by the method of fundamental solutions. To do this a particular solution must be obtained