Regularized Inversion of Noisy Laplace Transforms
Copyright policy )Regularized Inversion of Noisy Laplace Transforms
The authors 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. Noisy Laplace transforms arise in a wide variety of practical problems, for example in system theory and statistics. The paper contains an example from statistics-estimation of the mixing distribution, when a mixture of exponential distributions is observed.
- The University of Texas System United States
- Radboud University Nijmegen Netherlands
- Texas Tech University United States
mixture of exponential distributions, regularized inversion, Laplace transform, Applied Mathematics, rates of convergence, noisy Laplace transforms, regularization method, Mathematical Physics, Numerical methods for integral transforms, Numerical methods for ill-posed problems for integral equations
mixture of exponential distributions, regularized inversion, Laplace transform, Applied Mathematics, rates of convergence, noisy Laplace transforms, regularization method, Mathematical Physics, Numerical methods for integral transforms, Numerical methods for ill-posed problems for integral equations
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).31 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!