Bayesian Stable Mixture Model of State Densities of Generalized Chua's Circuit
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Savacı, Ferit Acar
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BRONZE
Green Open Access
Yes
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Abstract
In this paper, the probability density functions (PDFs) of the states of Generalized Chua's Circuit (GCC) have been modeled by Finite Mixture α-Stable (FMαS) distributions which is a Bayesian mixture model of α-stable distributions and it provides semiparametric characterization for the distributions of multiscroll chaotic attractors. Fully Bayesian approach has been applied to estimate the mixture parameters of multimodal distributions corresponding to the multiscroll chaotic attractors.
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Keywords
Semiparametric modeling, Probability density function, Chua's circuit, Multiscroll chaotic attractors, Chua's circuit, Probability density function, Multiscroll chaotic attractors, Semiparametric modeling
Fields of Science
0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 0101 mathematics, 01 natural sciences
Citation
Savacı, F. A., and Yılmaz, S. (2015). Bayesian stable mixture model of state densities of generalized Chua's circuit. International Journal of Bifurcation and Chaos, 25(3). doi:10.1142/S0218127415500388
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OpenCitations Citation Count
4
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25
Issue
3
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CrossRef : 2
Scopus : 4
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4
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892
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502
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