In this paper we construct a sequence of regularized inverses of the Laplace transform by relating this transform to a convolution operator for functions on the group of the positive real numbers with multiplication. Estimation of the mixing distribution, when a mixture of exponential distributions
On spline regularized inversion of noisy Laplace transforms
β Scribed by M Iqbal
- Publisher
- Elsevier Science
- Year
- 1997
- Tongue
- English
- Weight
- 511 KB
- Volume
- 83
- Category
- Article
- ISSN
- 0377-0427
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β¦ Synopsis
In this paper we have converted the Laplace transform to an integral equation of the first kind of convolution type, which is an ill-posed problem and used the spline regularization method to solve it. Inversion of perturbed Laplace transforms also plays an important role in system theory. The method is applied to several test examples taken from [1-3, 8, 11, 22]. It gives a good approximation to the true solution and compares well with the methods discussed in [1-3, 8, 11, 22]. The results are shown in Table 1 and respective diagrams.
π SIMILAR VOLUMES
In this paper we have converted the Laplace transform to an integral equation of the first kind of convolution type, which is an ill-posed problem and used the spline regularization method to solve it. The method is applied to several test examples taken from [J. Math. Comp. 53 (1989) 589; Inverse P
Shorter Communications truly circular leading edge but, as before, the stable shape is reached after about 0.4 sec. These observations can be compared with the results of the elegant experiment of WALTERS and DAVIDSON [l] where the initial motion of a two-dimensional bubble was observed without the
Most methods for the numerical calculation of inverse Laplace transformations f(t) = L -1 [F(s)] have serious limitations concerning the class of functions F(s) that can be inverted or the achievable accuracy. The procedures described in the paper can be used to invert rational as well as irrational
A new technique of inverting Moments and Laplace Transforms is presented, using a finite series of generalized Laguerre polynomials in the variable t = ln(1/x). The method is tested with two different functions, with particular emphasis on the estimation of errors involved. The applications of momen