Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/11

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Author: search.filters.author.Yılmaz, SerpilPublisher: search.filters.publisher.World Scientific Publishing Co. Pte Ltd

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  • Article
    Citation - WoS: 3
    Citation - Scopus: 4
    Stochastic bifurcation in generalized chua's circuit driven by skew-normal distributed noise
    (World Scientific Publishing Co. Pte Ltd, 2018) Yılmaz, Serpil; Savacı, Ferit Acar; Çek, Mehmet Emre; Savacı, Ferit Acar; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    In this study, the stochastic phenomenological bifurcations (P-bifurcations) of generalized Chua's circuit (GCC) driven by skew-normal distributed noise have been investigated by numerically obtaining the stationary distributions of the stochastic responses. The noise intensity and/or skewness parameters of skew-normal distributed noise have been chosen as the bifurcation parameters to change the structure of the stochastic attractor. While the number of breakpoints in the piecewise-linear characteristics of the GCC are fixed, it has been observed that the number of scrolls have been changed by tuning the noise intensity and the skewness parameter of the skew-normal distributed noise.
  • Article
    Citation - WoS: 4
    Citation - Scopus: 4
    Bayesian Stable Mixture Model of State Densities of Generalized Chua's Circuit
    (World Scientific Publishing Co. Pte Ltd, 2015) Savacı, Ferit Acar; Yılmaz, Serpil; Savacı, Ferit Acar; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    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.