Grafomotorické dovednosti (GA) představují skupinu psychomotorických procesů, které se zapojují během kreslení a psaní. GA jsou nutnou prerekvizitou pro zvládání základních školních schopností, konkrétně psaní. Děti v první a druhé třídě mohou mít potíže s prováděním jednoduchých grafomotorických úkolů (GD) a později ve třetí a čtvrté třídě také se samotným psaním (HD). Narušení procesů spojených se psaním je obecně nazýváno jako vývojová dysgrafie (DD). Prevalence DD v České republice se pohybuje kolem 3–5 %. V současné době je DD hodnocena subjektivně týmem psychologů a speciálních pedagogů. V praxi stále chybí objektivní měřicí nástroj, který by umožňoval hodnocení GD a HD. Z tohoto důvodu se tato disertační práce zabývá identifikováním symptomů spojených s grafomotorickou neobratností u dětí školního věku a vývojem nových parametrů, které je budou kvantifikovat. Byl vytvořen komplexní GA protokol (36 úloh), který představuje prostředí, ve kterém se mohou projevit různé symptomy spojené s GD a HD. K těmto symptomům bylo přiřazeno 76 kvantifikujících parametrů. Dále byla navrhnuta nová škála grafomotorických obtíží (GDRS) založena na automatizovaném zpracování online píma. Nakonec byla prezentována a otestována nová sada parametrizačních technik založených na Tunable Q Factor Wavelet Transform (TQWT). Parametry TQWT dokážou kvantifikovat grafomotorickou obratnost nebo nedostatečný projev v jemné motorice. GDRS přestavuje nový, moderní a objektivní měřící nástroj, který doposud chyběl jak v České republice, tak v zahraničí. Použití škály by pomohlo modernizovat jak diagnostiku DD, tak reedukační/remediační proces. Další výzkum by tento nástroj mohl adaptovat i do jiných jazyků. Navíc, tato metodologie může být použita a optimalizována pro diagnostiku dalších nemocí a poruch, které ovlivňují grafomotorické dovednosti, například pro autismus, poruchu pozornosti s hyperaktivitou (ADHD) nebo dyspraxii (DCD).

The thesis deals with one of the non-linear methods for signal processing - dynamic time warping (DTW). The method observes shape changes, which should be used in biomedical signals processing. The thesis involves the method description and consecution for finding DTW optimal way. The method is applied on the number series in the edutainment program, on the group of simulated signals and real electrocardiograms (ECG). ECG recordings were gained by performing experiments on the Masaryk University and their aim was clarifying the influence of voltage-sensitive dye on the heart tissue. One-lead ECG was described in time domain, frequency domain, time-frequency domain and subsequently remitted to DTW algorithm. The method outcomes evaluates the diversity rate of ECG signals obtained in each experiment stages. During the data evaluation were followed up the changes in process of the tension-sensible paint application and the stage of scouring toward control. The difference of elaborating signals group was verified in the time domain (37,5 %), in the frequency domain (75 %) and in the time-frequency domain (25 %). However, due to the small data group was not possible to explicitly approve the activity of voltage-sensitive dye on the heart tissue and to determinate limiting value of minimum algorithm way DTW for each heart round electrocardiogram classification. In the more data group analysis it is supposed to manifest the trend of growth heart round ECG differences in the stage of staining toward the stage of scouring.

The aim of this master's thesis is to get familier with problematic and concepts of econometrics (GDP, investment, usage and others). We see into used data mainly their characters and expectations and we discuss possibilities of frequention and time-frequention analysis of these data by Fourier and Wavelet transform. Data of quarter development of gross domestic product in Czech Republic, EU and USA will be analysed by the help of programm MATLAB. Data will be filtered by three ekonomic filters: Hodrick-Prescott, Baxter-King and Christiano-Fitzgerald filters. The aim is to find cyclic elements in developments of GDPs and to suggest an optimal type of analysis.

This thesis deals with the problem with cluster analysis and biosignal classification options. The principle of cluster analysis, methods for calculating distances between objects and the standard process in the implementation of clustering are described in the first part. For biosignals processing,it is necessary to get familiar with the primary parameters of these signals in the following sections of thesis, process biosignals and methods for recording of action potentials described. Based on studying different clustering methods is presented a program with the applied method kmedoid in the next section of this thesis. The steps of this program are described in detail and in the end of thesis functionality is tested on a database of signals ÚBMI.

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.

The first goal of diploma thesis is to study the basic principles of video signal compression. Introduction to techniques used to reduce irrelevancy and redundancy in the video signal. The second goal is, on the basis of information about compression tools, implement the individual compression tools in the programming environment of Matlab and assemble simple model of the video codec. Diploma thesis contains a description of the three basic blocks, namely - interframe coding, intraframe coding and coding with variable length word - according the standard MPEG-2.

This thesis focuses on image processing using wavelet transform. The usage of wavelet transform is analysed especially for image compression and image noise reduction purposes. The analysis describes in detail aspects and application of the following wavelet transform methods: CWT, DWT, DTWT, 2D DWT. The thesis further explains the meaning of the mother wavelet and studies certain specific kinds of wavelets, kinds of thresholding and its purposes and also touches on the JPEG2000 standard. Mathematica and Sage software packages were used to design algorithms for image compression and image noise reduction, utilising relevant wavelet transform findings. The concluding part of the thesis compares the two software packages and results obtained using different algorithms.

This thesis deals with time-frequency analysis of electrograms measured on isolated guinea pig hearts perfused according to Langendorff. Time-frequency analysis is based on algorithms Matching Pursuit and Wigner-Ville Distribution. The theoretical part describes the basics of electrocardiography, measurement on isolated hearts, the theory of approximation method Matching Pursuit and its combination with the Wigner-Ville distribution spectrum showing the energy density of the signal. Also other common approaches of time-frequency analysis are presented including the theory of continuous wavelet transform. The presented algorithms were tested on a set of electrograms, on which were induced ischemia within measurement followed by reperfusion. The proposed method allows for the fast detection of ischemia without any a priori knowledge of the signal, and also serves as a tool for measurement of EG important points and intervals. In the conclusion efficacy of the method was presented and its possible uses has been discussed.

The main object of this work is noise spectroscopy of CdTe radiation detectors (-rays and X–rays) and CdTe samples. The study of stochastic phenomenon and tracing redundant low-frequency noise in semiconductor materials require long-term measurements in time domain and evaluate suitable power spectral densities (PSD) with logarithmic divided frequency axes. We have used the means of time-frequency analysis derived from the discrete wavelet transform (DWT) and we have designed the effective algorithm for PSD estimation, which is comparable with an original analog method. CdTe single crystal with Au contacts we can imagine as a series connection of two Schottky diodes with a resistor between them. The bulk resistance at constant temperature and other constant parameters changes due to the carrier concentration changing only. The p-type CdTe sample shows metal behavior with every temperature changes. Semiconductor properties of the sample begin to dominate just after some period of time. This behavior is caused by the hole mobility changing. The voltage noise spectral density of 1/f noise depends on the quantity of free carriers in the sample. All the studied samples have very high value of low frequency noise, much higher than it should have been according to Hooge’s formula. The excess value of low frequency noise is caused by the low carrier concentration within the depleted region.

This thesis is focused on subject of image compression using wavelet transform. The first part of this document provides reader with information about image compression, presents well known contemporary algorithms and looks into details of wavelet compression and following encoding schemes. Both JPEG and JPEG 2000 standards are introduced. Second part of this document analyzes and describes implementation of image compression tool including inovations and optimalizations. The third part is dedicated to comparison and evaluation of achievements.