Picture of DNA strand

Pioneering chemical biology & medicinal chemistry through Open Access research...

Strathprints makes available scholarly Open Access content by researchers in the Department of Pure & Applied Chemistry, based within the Faculty of Science.

Research here spans a wide range of topics from analytical chemistry to materials science, and from biological chemistry to theoretical chemistry. The specific work in chemical biology and medicinal chemistry, as an example, encompasses pioneering techniques in synthesis, bioinformatics, nucleic acid chemistry, amino acid chemistry, heterocyclic chemistry, biophysical chemistry and NMR spectroscopy.

Explore the Open Access research of the Department of Pure & Applied Chemistry. Or explore all of Strathclyde's Open Access research...

Copulas for statistical signal processing (part II) : simulation, optimal selection and practical applications

Zeng, Xuexing and Ren, Jinchang and Sun, Meijun and Marshall, Stephen and Durrani, Tariq (2014) Copulas for statistical signal processing (part II) : simulation, optimal selection and practical applications. Signal Processing, 94. pp. 681-690. ISSN 0165-1684

[img] PDF (Copulas-Part2s-v2-5-2)
Copulas_Part2s_v2_5_2.pdf
Preprint

Download (2MB)

Abstract

This paper presents algorithms for generating random variables for exponential/Rayleigh/Weibull, Nakagami-m and Rician copulas with any desired copula parameter(s), using the direct conditional cumulative distribution function method and the complex Gaussian distribution method. Moreover, a novel method for optimal copula selection is also proposed, based on the criterion that for a given series of copulas, the optimal copula will have its copula density based mutual information closest to the corresponding bivariate distribution based mutual information. The corresponding bivariate distribution is the bivariate distribution that is used to derive this copula. Akaike information criterion (AIC) and Bayes’ information criterion (BIC) are compared with the proposed mutual information based criterion for optimal copula selection. In addition, several case studies are also presented to further validate the effectiveness of the copulas, which include dual branch selection combining diversity using Nakagami-m, exponential/Rayleigh/Weibull and Rician copulas with different marginal distributions as in real applications