National Repository of Grey Literature 2 records found  Search took 0.00 seconds. 
Muscle noise filtering in ECG signals
Novotný, Jiří ; Kubičková, Alena (referee) ; Smital, Lukáš (advisor)
This master's thesis deals with the optimization of numerical coefficients of the Wiener filter for muscle noise filtering in ECG signals. The theoretical part deals with ECG signal characteristic and muscle interference. It also contains a summary of the wavelet transform, wavelet Wiener's filtration, methods for calculating of the threshold and thresholding. In the last theoretical part the characteristic optimization techniques, the exhausive search and Nelder-Mead simplex method are mentioned, which were implemented in the practical part of this thesis in MATLAB. The functional verification and Wiener's filter optimization were tested on the standard electrocardiograms database CSE. By using the methods of exhausive search, the initial estimate for the solution method Nelder-Mead was obtained. The optimization method Nelder-Mead gives better results in the orders of hundredths or tenths than the method of exhausive search. The practical part is finished by the comparison of results of implemented algorithm with optimum coefficients, implemented in this thesis, with the results of other methods for filtering muscle interference in ECG signals.
Muscle noise filtering in ECG signals
Novotný, Jiří ; Kubičková, Alena (referee) ; Smital, Lukáš (advisor)
This master's thesis deals with the optimization of numerical coefficients of the Wiener filter for muscle noise filtering in ECG signals. The theoretical part deals with ECG signal characteristic and muscle interference. It also contains a summary of the wavelet transform, wavelet Wiener's filtration, methods for calculating of the threshold and thresholding. In the last theoretical part the characteristic optimization techniques, the exhausive search and Nelder-Mead simplex method are mentioned, which were implemented in the practical part of this thesis in MATLAB. The functional verification and Wiener's filter optimization were tested on the standard electrocardiograms database CSE. By using the methods of exhausive search, the initial estimate for the solution method Nelder-Mead was obtained. The optimization method Nelder-Mead gives better results in the orders of hundredths or tenths than the method of exhausive search. The practical part is finished by the comparison of results of implemented algorithm with optimum coefficients, implemented in this thesis, with the results of other methods for filtering muscle interference in ECG signals.

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