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Zpracování signálu srdečních ozev
Němcová, Simona ; Matějková, Magdaléna (oponent) ; Vondra, Vlastimil (vedoucí práce)
Tato bakalářská práce je zaměřena na zpracování signálu srdečních ozev. Popisuje princip vzniku srdečních ozev, způsoby jejich měření a především analýzu naměřeného fonokardiografického signálu. V praktické části práce je pomocí programového prostředí MATLAB navržen algoritmus pro detekci první a druhé srdeční ozvy, který je realizován hledáním maxima nebo těžiště u vyfiltrovaného fonokardiografického signálu.
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Time Frequency Analysis of ERP Signals
Bartůšek, Jan ; Provazník, Ivo (oponent) ; Černocký, Jan (vedoucí práce)
The aim of this work is to improve the algorithm for clustering ERP signals based on the temporal and spatial properties of pseudo-signals gained by the Independent Component Analysis. The main purpose is to find new features, which could improve the original algorithm. This study is investigating application of new features gained by Fourier Transform and short time Fourier Transform methods. Basic principle and performance of the concept is demonstrated on the sample algorithm. Results have shown that the method can bring a contribution to the original project and can be its convenient improvement.
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Identification of the parameters of an electroencephalographic recording system
Svozilová, Veronika ; Sekora, Jiří (oponent) ; Mézl, Martin (vedoucí práce)
Electroencephalographic recording system is used to examine a brain activity. Based on this examination we can establish the diagnosis of certain diseases, such as epilepsy. The purpose of this study has been the signal processing and a signal generation which were compared with the real signal. Artificially generated signal is based on Jansen‘s mathematical model which has been also implemented in MATLAB and then that model has been extended to more complex model including nonlinearities and model electrode – electrolyte. Also a signal measurements on EEG phantom and identification of the parameters of these signals were performed. Firstly a simply signals were tested and the identification of their parameters has served to validate the EEG phantom. Secondly the created signal designed by Jansen model were tested also. Besides an analysis of all signals includes the time frequency analysis or a superposition principle testing.
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Selected Aspects of Statistical Significance Testing in Time-Frequency Analysis
Klejmová, Eva ; Kohl,, Zdeněk (oponent) ; Fidrmuc, Jarko (oponent) ; Poměnková, Jitka (vedoucí práce)
This doctoral thesis is focused on analyses and assessment of the quality of the frequency and time-frequency transform of the data and the formulation of recommendations for working with such methods. When using these methods, the question arises of how to evaluate which components of the spectrogram are statistically significant and which are not. In this thesis, we analyze the properties of standard statistical significance tests. We discuss their advantages and disadvantages taking into account the heteroskedastic character of data. Based on our experiments we propose two types of improved testing methods that reduce the negatives standard tests. The final step is creating a framework for data filtering using our proposed methods.
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Selected Aspects of Statistical Significance Testing in Time-Frequency Analysis
Klejmová, Eva ; Kohl,, Zdeněk (oponent) ; Fidrmuc, Jarko (oponent) ; Poměnková, Jitka (vedoucí práce)
This doctoral thesis is focused on analyses and assessment of the quality of the frequency and time-frequency transform of the data and the formulation of recommendations for working with such methods. When using these methods, the question arises of how to evaluate which components of the spectrogram are statistically significant and which are not. In this thesis, we analyze the properties of standard statistical significance tests. We discuss their advantages and disadvantages taking into account the heteroskedastic character of data. Based on our experiments we propose two types of improved testing methods that reduce the negatives standard tests. The final step is creating a framework for data filtering using our proposed methods.
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Time Frequency Analysis of ERP Signals
Bartůšek, Jan ; Provazník, Ivo (oponent) ; Černocký, Jan (vedoucí práce)
The aim of this work is to improve the algorithm for clustering ERP signals based on the temporal and spatial properties of pseudo-signals gained by the Independent Component Analysis. The main purpose is to find new features, which could improve the original algorithm. This study is investigating application of new features gained by Fourier Transform and short time Fourier Transform methods. Basic principle and performance of the concept is demonstrated on the sample algorithm. Results have shown that the method can bring a contribution to the original project and can be its convenient improvement.
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Zpracování signálu srdečních ozev
Němcová, Simona ; Matějková, Magdaléna (oponent) ; Vondra, Vlastimil (vedoucí práce)
Tato bakalářská práce je zaměřena na zpracování signálu srdečních ozev. Popisuje princip vzniku srdečních ozev, způsoby jejich měření a především analýzu naměřeného fonokardiografického signálu. V praktické části práce je pomocí programového prostředí MATLAB navržen algoritmus pro detekci první a druhé srdeční ozvy, který je realizován hledáním maxima nebo těžiště u vyfiltrovaného fonokardiografického signálu.
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Identification of the parameters of an electroencephalographic recording system
Svozilová, Veronika ; Sekora, Jiří (oponent) ; Mézl, Martin (vedoucí práce)
Electroencephalographic recording system is used to examine a brain activity. Based on this examination we can establish the diagnosis of certain diseases, such as epilepsy. The purpose of this study has been the signal processing and a signal generation which were compared with the real signal. Artificially generated signal is based on Jansen‘s mathematical model which has been also implemented in MATLAB and then that model has been extended to more complex model including nonlinearities and model electrode – electrolyte. Also a signal measurements on EEG phantom and identification of the parameters of these signals were performed. Firstly a simply signals were tested and the identification of their parameters has served to validate the EEG phantom. Secondly the created signal designed by Jansen model were tested also. Besides an analysis of all signals includes the time frequency analysis or a superposition principle testing.
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