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IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences
Article . 2011 . Peer-reviewed
Full-Text: http://www.jstage.jst.go.jp/article/transfun/E94.A/4/E94.A_4_1133/_pdf
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IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences
Article . 2011 . Peer-reviewed
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DBLP
Article . 2011
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https://dx.doi.org/10.1587/tra...
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On Gaussian Product Modulus Distribution

descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 2011 English Publisher:Institute of Electronics, Information and Communications Engineers (IEICE)Journal:IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, volume E94-A, pages 1,133-1,135 (issn: 0916-8508, eissn: 1745-1337, Copyright policy )
Authors: KOIKE, Shin'ichi;

doi: 10.1587/transfun.e94.a.1133

On Gaussian Product Modulus Distribution

Abstract

In this letter, we derive a probability density function (PDF) for a modulus of product of two complex-valued Gaussian random variables. The PDF is expressed using Modified Bessel Functions, and the probability distribution is named Gaussian Product Modulus Distribution. Some examples of expectation calculation are provided.

Keywords

Gaussian random variable, modulus, product, PDF

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selected citations
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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).
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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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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