2011
DOI: 10.2478/s13540-011-0017-5
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Mollification of fractional derivatives using rapidly decaying harmonic wavelet

Abstract: We study the use of the wavelet expansion in terms of Meyer's wavelet to the problem of mollification in the numerical calculation of fractional derivative. It is shown that, when the simplest of Meyer's wavelet is used, the expansion is equivalent to the transform by the de la Vallée Poussin kernel, that was proposed by Hào et al. It is expected that better results are attained by using the rapidly decaying harmonic wavelet, which is another of Meyer's wavelet. We examine this. It is also shown that there exi… Show more

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Cited by 6 publications
(20 citation statements)
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“…It was shown that the use of the simplest of Meyer's wavelets agrees with the use of de la Vallée Poussin kernel adopted by Hào et al [2]. In [2,3], the calculation of fractional derivative D λ f (x) for λ > 0 was studied, which is generally an ill-posed problem. When f ϵ involving noise is given in place of smooth f , we calculate D λ [M f ϵ ](x), which approximates D λ f (x).…”
Section: Introductionmentioning
confidence: 99%
See 4 more Smart Citations
“…It was shown that the use of the simplest of Meyer's wavelets agrees with the use of de la Vallée Poussin kernel adopted by Hào et al [2]. In [2,3], the calculation of fractional derivative D λ f (x) for λ > 0 was studied, which is generally an ill-posed problem. When f ϵ involving noise is given in place of smooth f , we calculate D λ [M f ϵ ](x), which approximates D λ f (x).…”
Section: Introductionmentioning
confidence: 99%
“…When f ϵ involving noise is given in place of smooth f , we calculate D λ [M f ϵ ](x), which approximates D λ f (x). In [2,3], we estimate how the error of this approximation can be reduced by the choice of the scale on which µ depends.…”
Section: Introductionmentioning
confidence: 99%
See 3 more Smart Citations