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	Suppression of powerline interference in ECG signals Lacko, Michal ; Hrubeš, Jan (referee) ; Kozumplík, Jiří (advisor) This project includes survey of various methods ECG signal filtering, to suppress of powerline interference. It is specialized especially on properties which affecting the quality of filtration. The main essence of project is evaluation of the proposed methods in terms of quality and the least possible distortion of the resulting ECG signal. The work is focused on linear, adaptive filtering and filtering using discrete wavelet trans-form. Signal processing and evaluation of descriptive parameters are transferred using the graphical interface GUI in the program Matlab 7.7.0 ( R2008b ). Detailed record
	Adaptive controllers with principles of artificial intelligence and its comparison with classical identifications methods Dokoupil, Jakub ; Malounek, Petr (referee) ; Pivoňka, Petr (advisor) This piece of work deals with a philosophy of design adaptive controller, which is based on knowledge of mathematical model controlled plant. This master thesis is focused on closed-loop on-line parametric identification methods. An estimation of model´s parametres is solved by two main concepts: recursive leastsquare algorithms and neural estimators. In case of least-squares algorithm the strategy of preventing the typical problems are solved here. For instance numerical stability, accurecy and restricted forgetting. Back Propagation and Marquardt- Levenberg algorithm were choosen to represent artificial inteligence. There is still a little supermacy on the side of methods based on least-squares algorithm. To compare individual algorithms the grafical interface in MATLAB/Simulink was created. Detailed record
	Adaptive data compression by neural networks Kučera, Michal ; Přinosil, Jiří (referee) ; Koula, Ivan (advisor) Point of the work is using of neural networks for the datecompression. This brings new possibilities as by lossless as lossy compression. Draft of a few compress algorithm show the behaviour, advantages and weak points of these systems. As the solution we use knowledge of the layered perceptron Network and we try by the change of the structure and subparameters to teach such network to compress the data, according to our entry requirement. These networks have also advantages, which are meanwhile impediment to the using practically. The goal of this is to try some algorithms, look into their characteristics and posibility of the using. Then propose next posibility solutions and upgrading of these algorithms. Detailed record

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