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Wavelet Wiener filter of ECG signals
Sedláčková, Eva ; Odstrčilík, Jan (referee) ; Smital, Lukáš (advisor)
The aim of this work is introduction with method of filtering the ECG signals using wavelet transformation and use of this method for filtering of signal disturbed with myopotencials. The work deals with general properties and with genesis of ECG signals and describes ECG curve. Next part of work is focused on wavelet transformation, types of wavelet transformation and different methods calculation thresholds and thresholding. Design part of work is focused on design Wiener filter for remove myopotencials from ECG signals and finding optimal parameters of this filter using optimization algorithm. For optimization is used simplex method. Discovered optimal parameters are assessed on CSE and MIT-BIH Arrhythmia database and compared with results of other authors.
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Filtering methods for NMR measurements
Nezhyba, Jiří ; Mikulka, Jan (referee) ; Gescheidtová, Eva (advisor)
This master’s thesis deals with the wavelet transform and its use in processing and removing noise from images acquired by nuclear magnetic resonance. It defines fundamental terms for this work as mother wavelet or thresholding. Above all, it describes the principle of wavelet transform, thresholding techniques and criteria for evaluating the effectiveness of filtration. It describes the relation between wavelet transforms and digital filter banks. The experimental section describes the designed filtering method for removing noise from an image captured by the technique of nuclear magnetic resonance. We applied to different kinds of mother wavelets. Evaluation of the effectiveness of filtering was performed using the signal to noise ratio, relative contrast and the steepness of the intensity changes in signal intensity. It also discusses the comparison of properties of the image and selecting the mother wavelets based on image characteristics. Images were compared in terms of a histogram, cumulative histogram, k-space and the difference image.
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MR image processing
Mrákava, Petr ; Smékal, Zdeněk (referee) ; Gescheidtová, Eva (advisor)
The subject of this bachelor's thesis is to become familiar with the methods of processing image acquired by techniques of nuclear magnetic resonance. It describes the gradual steps in the digitizing of the signal to the image data. But in the process a disturbing component is almost always created in the image, in particular noise, which causes image devaluation. Therefore, further work is focused mainly on eliminating present disturbing components. For the noise elimination, the widely used wavelet transformation is applied, which is implemented by banks of digital filters. The experimental part of this work deals with design of MR filtering method, optimal filtering parameters setting, decomposition of images into magnetic field map, and subsequent comparison of results obtained.
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Solution of complex problems using evolutionary algorithms
Belovič, Boris ; Atassi, Hicham (referee) ; Burget, Radim (advisor)
Difficult problems are tasks which number of possible solutions increase exponentially or factorially. Application of common mathematical methods for finding proper solution in polynomial time is ineffective. Signal prediction is an example of diffucult problem. Signal is represented with a time serie and there is no explicit mathematical formula describing the signal. When genetic algorithms are applicated, they try to discover hidden patterns in time serie. These patterns can be used for prediction. Implication rules are used for discovery of these hidden patterns in time serie. Each rule is represented by one chromosome in population. Rules consist of two parts: conditional part and result part. Rules in population are compared with time serie and then the rules are evaluated according to their success in prediction. After the evaluation of rules, simulated evolution is started. Result of this evolution process is a group of rules which represent the most distinct patterns in time serie. These rules are then validated on validation set. Application is implemented in JAVA programming language.
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Wavelet transform based object detector
Mikuš, Ondřej ; Průša, Zdeněk (referee) ; Rajmic, Pavel (advisor)
This thesis deals with applying methods on object detection in image. Separation of objects off the background is often needed during the image processing. It isolates the region of interest that can be worked with. The main purpose of this paper is the explanation of principles of pre-processing and segmentation of image, resulting in object detection using the wavelet transformation. This wavelet transformation is described more in detail, because it is the base of the primary used method. In the practical part of this thesis the main method was implemented to MATLAB environment and tested on set of images. The method was tested for robustness against noise and blur of image. It was compared with commonly used methods, using the edge detectors and thresholding. A simulation program was created for comparison of methods efficiency, including user interface.
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Analysis of acoustic and electromagnetic emission signals
Boudný, Petr ; Káňa, Ladislav (referee) ; Sadovský, Petr (advisor)
Master´s thesis is focused to analyse the acoustic and electomagnetic emission signals. These signals generate external power applied on the material. This power put there plastic deformation and create cracks. Spectral analyse show that signals are non-stationary. Wavelet transformation was used to spectral analyse which informate about time-frequence vaules of the signal.
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Processing of images of early spruce needles scanned by MR technology
Raichl, Jaroslav ; Říha, Kamil (referee) ; Gescheidtová, Eva (advisor)
This semester project deals with filtering of the images detected by use of NMR obtained by NMR application measurement of nuclear magnetic resonance (NMR). This thesis includes the theory of nuclear magnetic resonance, digital filters, basic digital filter banks structures, theory of Wavelet transformation and description of Signal to Noise Ratio calculation. Basic procedure of the MR signal denoising is summarized in the theoretical part of the thesis. The denoising of the images detected by nuclear magnetic resonance is described. In experimental part filtering methods for images denoising are described, which are implemented in program Matlab. These methods are based on Wavelet transformation, digital filter banks with proper thresholding. Effectiveness of filtering methods designed was verified on 2D NMR images. All of these 2D images were measure on MR tomography in the Institute of Scientific Instruments Academy of Science of the Czech Republic in Brno.
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Filtering methods for MR images processing
Pláněk, Jiří ; Smékal, Zdeněk (referee) ; Gescheidtová, Eva (advisor)
This master´s thesis deals with wavelet transformation and its signal and image noise reduction application method. Significant parameters problems as a wavelet type, a threshold technique selection, a threshold level and a level analysis selection for successful signal and noise image filtering are described. A relation between wavelet transformation and digital bank filter is used by anti-noise and sub-bandwidth filtration. A part of the master´s thesis is focused on nuclear magnetic resonation, where jaw-joint image is processed. Jaw joint image noise reduction filtration methods are used in experimental part of the master´s thesis. Consequently, filtration methods improve a jaw joint image quality, which helps a doctor with patient health state condition. Different types of wavelets were tested and in different application methods order. Filtration methods results were visually compared; therefore any conclusion comparison has subjective matter. Accordingly, only doctor is able to resolve which filtration method is convenient to use to determine patient health state.
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