Analysis of cerebral microcirculation dynamics with the application of nonlinear time series methods

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Supervisor:
Homlok József
Department of Control Engineering and Information Technology

My thesis summarizes the mapping of biological systems in mathematical and theoretical way on non-linear and dynamic systems. Sometimes in the human body the physiological parameters can not be tested directly. One can determine the causes and consequences if the measured parameters and the initial conditions are in place. In this paper I got to know a process, which we do not know for sure neither the structure nor the parameters. In case of chaotic systems enough one measurable parameter, than one can inferred the system and thus the underlying physiological processes usually with a statistic method. The aim is estimate a quantitative value for the cerebral microcirculation dynamics with nonlinear time series analysis methods. The thesis contains mathematical descriptions and some direct application for time series analysis methods with the real measured data of the cerebral microcirculation. This paper uses a publicly available software TISEAN for creating numerical calculations and estimations.

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