1998•Electronics LettersRequires access

Modelling signals of arbitrary kurtosisfor testing BSS methods

Vicente Zarzoso, Asoke Kumar Nandi

Open publisher page 7 citations

Abstract

It is shown how a very simple distribution, the Bernoulli random variable, exhibits all possible normalised kurtosis values when varying the probability of its two events. This result means that signals of any normalised kurtosis may be modelled by this distributiori, which is of relevance within the framework of blind source separation based on fourth-order cumulants.

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What this paper is about

It is shown how a very simple distribution, the Bernoulli random variable, exhibits all possible normalised kurtosis values when varying the probability of its two events. This result means that signals of any normalised kurtosis may be modelled by this distributiori, which is of relevance within the framework of blind source separation based on fourth-order cumulants.

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OpenAlex reports 7 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

It is shown how a very simple distribution, the Bernoulli random variable, exhibits all possible normalised kurtosis values when varying the probability of its two events. This result means that signals of any normalised kurtosis may be modelled by this distributiori, which is of relevance within the framework of blind source separation based on fourth-order cumulants.

Key concepts: Kurtosis, Cumulant, Higher-order statistics, Random variable, Bernoulli's principle, Algorithm, Mathematics, Independent component analysis

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