Master Degree / Yüksek Lisans Tezleri

Permanent URI for this collectionhttps://hdl.handle.net/11147/3008

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Access Right: Open AccessSubject: search.filters.subject.Chaotic behavior in systems

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Now showing 1 - 4 of 4
  • Master Thesis
    Implementation of Synchronized Chaotic Systems by Field Programmable Gate Array
    (Izmir Institute of Technology, 2008) Eroğlu, Can; Savacı, Ferit Acar
    In this thesis, the geometric properties of chaotic systems are used to determine their synchronization. First, each system is constructed with MATLAB Simulink blocks. Afterwards, feedback control system for synchronization of chaotic systems is proposed by using complete synchronization approach. In the next stage, Simulink designs are translated into System Generator design so that bitstream file which is used to program FPGA is obtained. Finally, the design is implemented into FPGA by dowloading bitstream file into FPGA. As an application of FPGAs the synchronization of chaotic systems have been achieved.
  • Master Thesis
    Design of Nonlinear Observer for Chaotic Message Transmission
    (Izmir Institute of Technology, 2014) Çobanlar, Muhammed; Tatlıcıoğlu, Enver
    Chaos is an interesting nonlinear phenomena that occurs in wide variety of fields. A significant amount of research was devoted to understanding chaos and its properties. After that, researchers focused on searching for possible application areas for chaos to utilize its properties. The need to increase the security of a communication system is considered as a perfect match for chaos and its several properties, yielding chaotic communication. In this thesis, chaotic communication is approached from a control theory perspective. Specifically, three nonlinear observers are designed to extract message encrypted in a chaotic communication signal. The design and stability analysis is presented for the first observer, and the other observers are presented as modifications to the first one. Extensive numerical simulations are performed to demonstrate the viability of the proposed observers. Robustness of the observers to noise, additive disturbances, and parametric mismatch, and security of the observers are demonstrated numerically.
  • Master Thesis
    Stochastic Resonance in Chua's Circuit Driven by Alpha-Stable Noise
    (Izmir Institute of Technology, 2012) Yılmaz, Serpil; Savacı, Ferit Acar
    The main aim of this thesis is to investigate the stochastic resonance (SR) in Chua's circuit driven by alpha-stable noise which has better approximation to a real-world signal than Gaussian distribution. SR is a phenomenon in which the response of a nonlinear system to a sub-threshold (weak) input signal is enhanced with the addition of an optimal amount of noise. There have been an increasing amount of applications based on SR in various fields. Almost all studies related to SR in chaotic systems assume that the noise is Gaussian, which leads researchers to investigate the cases in which the noise is non-Gaussian hence has infinite variance. In this thesis, the spectral power amplification which is used to quantify the SR has been evaluated through fractional lower order Wigner Ville distribution of the response of a system and analyzed for various parameters of alpha-stable noise. The results provide a visible SR effect in Chua’s circuit driven by symmetric and skewed-symmetric alpha-stable noise distributions. Furthermore, a series of simulations reveal that the mean residence time that is the average time spent by the trajectory in an attractor can vary depending on different alpha-stable noise parameters.
  • Master Thesis
    Analysis of Observed Chaotic Data
    (Izmir Institute of Technology, 2004) Çek, Mehmet Emre; Savaci, Ferit Acar
    In this thesis, analysis of observed chaotic data has been investigated. The purpose of analyzing time series is to make a classification between the signals observed from dynamical systems. The classifiers are the invariants related to the dynamics. The correlation dimension has been used as classifier which has been obtained after phase space reconstruction. Therefore, necessary methods to find the phase space parameters which are time delay and the embedding dimension have been offered. Since observed time series practically are contaminated by noise, the invariants of dynamical system can not be reached without noise reduction. The noise reduction has been performed by the new proposed singular value decomposition based rank estimation method.Another classification has been realized by analyzing time-frequency characteristics of the signals. The time-frequency distribution has been investigated by wavelet transform since it supplies flexible time-frequency window. Classification in wavelet domain has been performed by wavelet entropy which is expressed by the sum of relative wavelet energies specified in certain frequency bands. Another wavelet based classification has been done by using the wavelet ridges where the energy is relatively maximum in time-frequency domain. These new proposed analysis methods have been applied to electrical signals taken from healthy human brains and the results have been compared with other studies.