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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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Static image enhancement using wavelet transform
Candrák, Matúš ; Rajmic, Pavel (referee) ; Smékal, Zdeněk (advisor)
In tomography and ultrasound signal processing, there is the noise build-up into the processing. Bachelor's thesis deals with static images highlighting, with denoising using wavelet transformation and edge detection with basic operators. This work describes some types of wavelts used for denoising of image and basic operators for edge detection in the image. The last part deals with a particular application for image processing, which was created in MATLAB.
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ECG quality estimation
Pospíšil, Jan ; Smíšek, Radovan (referee) ; Smital, Lukáš (advisor)
This bachelor thesis deals with the question of estimation of the quality of the ECG signals, which is a key parameter for determining the diagnosis. The theoretical part deals with the basic knowledge concerning cardiac physiology, electrocardiography and finally the types of interferences that can occur during the measurement. The following practical part will deal with the published methods and the proposal of methods for estimating signal quality and their testing on artificial and real data.
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Image noise reduction method based on discrete wavelet transform
Holiš, Michal ; Přinosil, Jiří (referee) ; Malý, Jan (advisor)
This bachelor's thesis contains theoretical treatise on noises, which occur in digital visual data, their classification and possibilities of their removal. The next part is applied to theory of wavelets, wavelet transforms and their usage in working with one-dimensional, but mostly with two-dimensional signals. It is than mainly applied on visual data with a view to removing of failures contained in these data. The last part of the thesis is about implementation of demonstrational programme. This programme is created for removing of noise from the chosen visual data on the basis of user's chosen variables.
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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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Evolutionary Optimization of the EEG Classifier Feature Extractor
Ovesná, Anna ; Hurta, Martin (referee) ; Mrázek, Vojtěch (advisor)
This work focuses on the optimisation of EEG signal classification of alcoholics and control subjects using evolutionary algorithms with a multi-objective approach. The main goal is to maximise the accuracy, sensitivity and specificity of the classification algorithm and minimise the number of features used. Four different classifiers are used, namely Support Vector Machine, k-nearest neighbors, Naive Bayes and AdaBoost. The selection of the best features is optimised using three different evolutionary approaches, two of which convert multi-objective optimisation to single-objective using weighted summation or restricting the maximum number of features. The Pareto optimal solutions are found by the NSGA-II algorithm. Results show that the evolutionary algorithms, combined with appropriate classifiers, reliably distinguish a person with a tendency to alcoholism from one with a healthy relationship towards alcohol.
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Time-scale analysis of sovereign bonds market co-movement in the EU
Šmolík, Filip ; Vácha, Lukáš (advisor) ; Krištoufek, Ladislav (referee)
The thesis analyses co-movement of 10Y sovereign bond yields of 11 EU mem- bers (Greece, Spain, Portugal, Italy, France, Germany, Netherlands, Great Britain, Belgium, Sweden and Denmark) divided into the three groups (the Core of the Eurozone, the Periphery of the Eurozone, the states outside the Eurozone). In the center of attention are changes of co-movement in the crisis period, especially near the two significant dates - the fall of Lehman Brothers (15.9.2008) and the day, when increase of Greek public deficit was announced (20.10.2009). Main contribution of the thesis is usage of alternative methodol- ogy - wavelet transformation. It allows to research how co-movement changes across scales (frequencies) and through time. Wavelet coherence is used as well as wavelet bivariate and multiple correlation. The thesis brings three main findings: (1) co-movement significantly decreased in the crisis period, but the results differ in the groups, (2) co-movement significantly differs across scales, but its heterogeneity decreased in the crisis period, (3) near to the examined dates sharp and significant decrease of wavelet correlation was observable across lower scales in some states. JEL Classification C32, C49, C58, H63 Keywords Co-movement, Wavelet Transformation, Sovereign Debt Crisis, Sovereign Bond Yields,...
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Person Identification and Verification Using EEG
Žitný, Roland ; Orság, Filip (referee) ; Tinka, Jan (advisor)
The aim of this work was to create a brain-computer interface that reliably identifies and verifies a person using his electroencephalographic signals. Creating a user profile and verifying it is based on processing reactions to his own face, and the face of strangers or acquaintances. Algorithms such as bandpass and noise removal using wavelet transformation are user to filter signals. The classification of reactions is performed using a convolutional neural network or linear discriminant analysis. The average accuracy of the linear discriminant analysis is 66.2 % and of the convolutional neural network is 58.7 %. The maximum achieved accuracy was with linear discriminant analysis and at 93.7 %.
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Fetal ECG records analysis
Hláčiková, Michaela ; Smíšek, Radovan (referee) ; Smital, Lukáš (advisor)
This thesis is focused on the analysis of fetal ECG records measured by indirect method from mother´s abdomen. The thesis consists of the theoretical part is focused on fetal, heart development and description of fetal ECG signal. This thesis also offers an overview of fECG signal processing methods used nowadays. The practical part of the thesis deals with the implementation of algorithms based on wavelet transformation and Least Mean Square LMS method in Matlab programming environment. The final part of the thesis consists of the analysis of achieved results.
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