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Kalman-Bucy Filter in Continuous Time
Týbl, Ondřej ; Maslowski, Bohdan (advisor) ; Čoupek, Petr (referee)
In the Thesis we study the problem of linear filtration of Gaussian signals in finite-dimensional space. We use the Kalman-type equations for the filter to show that the filter depends continuously on the signal. Secondly, we show the same continuity property for the covariance of the error and verify existence and uniqueness of a solution to an integral equation that is satisfied by the filter even under more general assumptions. We present several examples of application of the continuity property that are based on the theory of stochastic differential equations driven by fractional Brownian motion. 1
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Suppression of power-line interference in ECG signals
Gregorová, Kateřina ; Vítek, Martin (referee) ; Kozumplík, Jiří (advisor)
This work includes an overview of the different methods of filtering of ECG signals that suppress the network interference. It focuses on the parameters that affect the quality of filtration for the three main groups of filters: FIR, IIR and adaptive filters. The main objective is to evaluate proposed methods in terms of the quality of filtration. This quality is rated an average output SNR, standard deviation and time filtering. The criteria of success is based on the filtration of the basic requirements on digital filters. Design of filter is realized in the Matlab programming environment.
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Linear and Adaptive Filters for ECG Signals
Kubát, Milan ; Lamoš, Martin (referee) ; Kozumplík, Jiří (advisor)
In this work, I deal with ECG signal interference suppression using linear and adaptive filters. This falls in field of signal preprocessing. The aim is to properly filter the signal, while maintaining its diagnostic value. I designed filters based on spectral lines resetting, Lynn’s filters and two types of adaptive filters. In the next part, results of different filtering ways are compared.
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Wavelet Filtering of ECG Signals
Staša, Josef ; Kolář, Radim (referee) ; Kozumplík, Jiří (advisor)
The aim of this project is introduction to problems about filtering of signals using wavelet transform. This method is very effective and in present it is often exploited. The main imposition is to use wavelet transform for filtering of ECG signals. Practical part of my project is realized wiener filtering based on DTWT in MATLAB software, to show advantages, disadvantages and compare linear filtering .
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Narrow Band Filtering of ECG Signals
Ryšánek, Jan ; Provazník, Ivo (referee) ; Kozumplík, Jiří (advisor)
This work deals with ECG signal preprocessing. Purpose of the preprocessing is adjustment of signal which is favorable for its subsequent analysis. The objective of this work is to filter the ECG signal by suitable methods of linear and adaptive filtering leading to the suppression of unwanted interference. The next step is to compare different degrees of success filtering thanks to results which were reached by the indivudual methods. Criterions of success filtering are based on the basic requirements for digital filters. Design of filters is realized in matlab programme. To realization is used FIR and IIR type of filters and adaptive type of filters
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Removing baseline wander in ECG with empirical mode decomposition
Procházka, Petr ; Kolářová, Jana (referee) ; Kubičková, Alena (advisor)
In this semestral thesis, realizations of chosen linear filters for baseline wander are described. These filters are then used on artificial ECG signals from CSE database with added baseline wander. These methods are compared and results are evaluated. After that, literature search of Empirical mode decomposition method is utilized. Realization of designed filters in MATLAB programming language are described, then results are evaluated with respect to filtration success.
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Speckle noise suppression methods in ultrasound images
Tvarůžek, Marek ; Harabiš, Vratislav (referee) ; Mézl, Martin (advisor)
This diploma thesis deals with the methods of despeckling in ultrasound images. Ultrasound imaging and related artifacts are described in more details. Ultrasound imaging has its pros and cons, where speckle noise is a disadvantage to be solved. Models of origin of this specific noise are referred too. Practical part of this thesis aims on filtering speckled images by basic and advanced filtering methods as are linear filtering, median filtering, application of Frost filter, QGDCT, geometric filtering, anisotropic diffusion filtering and filtering based on wavelet transformation. Results are compared on the basis of objective criteria.
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Wavelet filtering of ECG Signals
Ryšánek, Jan ; Smital, Lukáš (referee) ; Kozumplík, Jiří (advisor)
This work deals with the possibilities of filtering the ECG signal, representing the first part, which is the basis for successful delineation and follow diagnosis of the ECG signal. Filtration in this case is mean to suppress interference from electrical grid, noise of electrical grid. The content of the work is description of filters realized trough wavelet transform and linear filtering as a means to successful filtration of interference. There are method of stationary wavelet transform - dyadic wavelet transform, wavelet packet transform and wavelet wiener filtering method. Linear filtering includes two narrow-band FIR filters. The objective of this work is to propose different methods of wavelet and linear filters in Matlab, filtering of ECG signals and compare the success of filtration methods. ECG signals used in this work are from the CSE database.
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Wavelet filtering of ECG Signals
Šugra, Marián ; Smital, Lukáš (referee) ; Kozumplík, Jiří (advisor)
This masters thesis is focused on filtering the ECG signal for suppression of spurious frequency components of the network. The theoretical part is talking about electrocardiography, ECG signal interference and about principle different types of filtration. In practical part of this thesis are described linear filtering methods and wavelet transform methods with discrete time. The main topic of this work is recommended the best type of filtration.
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