Paper
3 April 2008 Finite mixture models for ultra-wideband channels
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Abstract
In this paper we estimate finite mixture models (FMM) to describe the statistics of the ultrawideband (UWB) channel amplitudes. Various combinations of Rayleigh, Nakagami, Weibull, and Lognormal distributions are used to form the constituent probability density functions (PDFs) of the FMMs. The FMMs are identified using the Stochastic Expectation Maximization (SEM) algorithm. Akaike's Information Criterion is used to compare the quality of data fit provided by the FMMs and models containing only one distribution (non-mixtures). The results indicate that UWB channel amplitude statistics are best represented by mixtures of Rayleigh, Lognormal and Weibull PDFs.
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Divya Choudhary and Aaron Robinson "Finite mixture models for ultra-wideband channels", Proc. SPIE 6980, Wireless Sensing and Processing III, 69800Q (3 April 2008); https://doi.org/10.1117/12.793419
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KEYWORDS
Data modeling

Statistical modeling

Expectation maximization algorithms

Stochastic processes

Scanning electron microscopy

Antennas

Process modeling

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