In this paper, we present an analytical approximation to positive a-stable probability distribution functions, which in general do not possess a compact analytical form. Our approximation is based on decomposing a positive a-stable random variable into a product of a Pearson and another positive stable random variable. This decomposition allows one to approximate any positive stable pdf as a mixture of Pearson densities, hence providing an analytical representation. This representation allows one to employ maximum likelihood estimation and Bayesian techniques in the presence of positive a-stable noise or signals. The efficiency of the decomposition is demonstrated by simulation studies.

Analytical representation for positive alpha-stable densities

Kuruoglu EE
2003

Abstract

In this paper, we present an analytical approximation to positive a-stable probability distribution functions, which in general do not possess a compact analytical form. Our approximation is based on decomposing a positive a-stable random variable into a product of a Pearson and another positive stable random variable. This decomposition allows one to approximate any positive stable pdf as a mixture of Pearson densities, hence providing an analytical representation. This representation allows one to employ maximum likelihood estimation and Bayesian techniques in the presence of positive a-stable noise or signals. The efficiency of the decomposition is demonstrated by simulation studies.
2003
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/57591
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