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Methods for electroencephalogram records comparison
Kliment, Juraj ; Ronzhina, Marina (referee) ; Janoušek, Oto (advisor)
The bachelor thesis deals with the comparison of EEG signals from the human brain. The aim of this work is to find suitable nonlinear parameters, based on which it is possible to compare EEG records created in different conditions. The selected parameters are then tested on data from a publicly available database using Matlab software, the results are statistically processed and compared with the results of existing scientific studies. The comparison was based on the parameters Approximate entropy, Correlation dimension, Hurst exponent and Lyapunov exponent.
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Methods for electroencephalogram records comparison
Kliment, Juraj ; Ronzhina, Marina (referee) ; Janoušek, Oto (advisor)
The bachelor thesis deals with the comparison of EEG signals from the human brain. The aim of this work is to find suitable nonlinear parameters, based on which it is possible to compare EEG records created in different conditions. The selected parameters are then tested on data from a publicly available database using Matlab software, the results are statistically processed and compared with the results of existing scientific studies. The comparison was based on the parameters Approximate entropy, Correlation dimension, Hurst exponent and Lyapunov exponent.
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Correlation dimension analysis for heart rate variability analysis
Ptáček, Ondřej ; Čmiel, Vratislav (referee) ; Janoušek, Oto (advisor)
Bachelor thesis deals with the analysis of heart rate variability (HRV). By focusing on the analysis of HRV in the time domain and mainly using correlation dimension. It is necessary to propose a methodology for evaluating changes in HRV data using these two techniques of analysis and the comparison of the two approaches. Subsequently create an application in MATLAB for analysis of HRV, which is able to evaluate the effect of changes in HRV caused by ischemia. In the last section it is necessary to discuss the results and the comparison of the two approaches to detect changes induced by ischemia.
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Methods for electroencephalogram records comparison
Kliment, Juraj ; Ronzhina, Marina (referee) ; Janoušek, Oto (advisor)
The bachelor thesis deals with the comparison of EEG signals from the human brain. The aim of this work is to find suitable nonlinear parameters, based on which it is possible to compare EEG records created in different conditions. The selected parameters are then tested on data from a publicly available database using Matlab software, the results are statistically processed and compared with the results of existing scientific studies. The comparison was based on the parameters Approximate entropy, Correlation dimension, Hurst exponent and Lyapunov exponent.
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Methods for electroencephalogram records comparison
Kliment, Juraj ; Ronzhina, Marina (referee) ; Janoušek, Oto (advisor)
The bachelor thesis deals with the comparison of EEG signals from the human brain. The aim of this work is to find suitable nonlinear parameters, based on which it is possible to compare EEG records created in different conditions. The selected parameters are then tested on data from a publicly available database using Matlab software, the results are statistically processed and compared with the results of existing scientific studies. The comparison was based on the parameters Approximate entropy, Correlation dimension, Hurst exponent and Lyapunov exponent.
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Correlation dimension analysis for heart rate variability analysis
Ptáček, Ondřej ; Čmiel, Vratislav (referee) ; Janoušek, Oto (advisor)
Bachelor thesis deals with the analysis of heart rate variability (HRV). By focusing on the analysis of HRV in the time domain and mainly using correlation dimension. It is necessary to propose a methodology for evaluating changes in HRV data using these two techniques of analysis and the comparison of the two approaches. Subsequently create an application in MATLAB for analysis of HRV, which is able to evaluate the effect of changes in HRV caused by ischemia. In the last section it is necessary to discuss the results and the comparison of the two approaches to detect changes induced by ischemia.
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The Distribution Mapping Functions
Jiřina, Marcel
The target of this study is to make clear the difference of the distribution mapping function introduced in 2003 and the classical notion of point processes theory, the counting function N, Ripley’s K-function, and other two distance functions, F and G-functions. We summarize here necessary starting points from the point process theory using the famous work by Baddeley, a two-volume book of Daley and Vere-Jones and short paper by Dixon. When dealing with the distribution mapping function we use up-to-date formulations used in various papers since 2003.
Fulltext: content.csg -  PDF
Plný tet: v1222-15 - PDF
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Klasifikátor založený na inverzních hodnotách indexů II. teorie a příloha
Jiřina, Marcel ; Jiřina jr., M.
A theory of a new method for the classification of data into classes is presented. The method is based on the sum of reciprocals of neighbors' indexes. We show that neighbors' indexes are in close relation to the approximate polynomial transform of the neighbors' distances. The sum of the reciprocals of indexes for all neighbors forms truncated harmonic series due to a finite number of its elements. For the neighbors of one class there is a sum of the selected elements of this truncated series. It is proved that the ratio of these sums gives just the probability that the point to be classified - the query point - is of that class.
Fulltext: content.csg - PDF
Plný tet: v1041-08 - PDF
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Klasifikátor založený na inverzních hodnotách indexů
Jiřina, Marcel ; Jiřina jr., M.
A new method for the classification of data into classes is presented. The method is based on the sum of reciprocals of neighbors' indexes. We show that neighbors' indexes are in close relation to the polynomial transform of the neighbors' distances. The sum of the reciprocals of indexes for all neighbors forms truncated harmonic series due to a finite number of its elements. For the neighbors of one class there is a sum of the selected elements of this truncated series. It is proved that the ratio of these sums gives just the probability that the point to be classified -- the query point -- is of that class. The classification ability is demonstrated on real-life data from the Machine Learning Repository and the results are compared with published results obtained through other methods.
Fulltext: content.csg - PDF
Plný tet: v1034-08 - PDF
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