The master thesis deals with the issue of gaining the respiratory rate from ECG and PPG signals, which are not only in clinical practice widely used measurable signals. The theoretical part of the work outlines the issue of obtaining a breath curve from these signals. The practical part of the work is focused on the implementation of five selected methods and their final evaluation and comparison.

Motivated by the need for less polluting energy production, the recent increase in renewable electricity production is reshaping classical power systems. Initially unidirectional and constant power flow becomes multi-directional and dynamic. As one of the many consequences, classical power system fault location methods might become outdated.To this extent, the development of new methods as well as improvement of already existing methods is of great interest. Additionally, robust and fast means of fault location strengthen power system reliability by improving recovery time. Since most of the faults occur at the distribution level, a study of the main fault location methods in distribution power systems is first conducted. Relevant information about their respective advantages and drawbacks put into light the need to improve classical fault location methods or to develop new methods. The main objective of the thesis is to develop a prototype data-driven ground fault location method that aims to improve the robustness and accuracy offault location in the power system, as well as offer new solutions for fault location. An 11-bus 20 kV distribution power system with distributed generation is modeled to test the method. As a requirement for data-driven methods, the dataset is provided through simulation where time-domain three-phase voltages at the system substation during fault are generated. This data is then processed using dyadic discrete wavelet transform, a powerful signal processing method, to extract useful information of the signal, after what relevant features are found from the wavelet coefficients. To predict the location ofthe fault, neural networks are trained to find potential correlations between computed features and the distance of the fault from the substation. After testing and comparing different combinations of neural networks, results are analyzed, and eventually, challenges and potential improvements for further development and application of the method are introduced.

This thesis deals with discrete wavelet transform of a two dimensional discrete signal using the CDF9/7 wavelet. It contains theoretical principles of discrete wavelet transformation, a description of the convolution and Lifting calculation principle, characteristics of the CDF9/7 wavelet, the possibilities of processing a two dimensional input signal and boundary handling. Both principles (convolution, Lifting) of the calculation of two dimensional discrete wavelet transformation have been implemented within the thesis using the CDF9/7 wavelet in the C++ and Java programming languages. Four applications have been created that way which have been described in detail and then compared with one another especially in light of the calculation speed of discrete wavelet transformation. Finally an analysis of the acquired results and an evaluation of the whole thesis has been performed.

This diploma thesis deals with location optimal wavelet for detecton charakterics points of QRS complex in ECG signals. The first part of this thesis deals with description of heart, genesis of electric signals on heart and problem of noise. The second part describes the wavelet transform and the designed program and the third part evaluate detection results. The created program is working with 10 ECG signals from the CSE database and is testing 12 different mother wavelets. The program was developed in Matlab environment and is based on the finding zero-points in the transformed signal.

This work deals with ECG signal measuring and methods of its processing. It compares some of the QRS detection methods and describes some of the testing databases. In this work a detector of QRS complex is realized, it is based on the approach of zero crossings. Next section makes combination of results from separate leads to one, which improves efficiency of detection. One section of this work deals with design and realization delination of ECG signal. In the last part outputs of this delineation are compared with the results of the other authors.

This thesis deals with a proposition of an algorithm for QRS complex and typical ECG waves boundaries detection. It incorporates a literature research focused on heart electrophysiology and commonly used methods for ECG fiducial points detection and delineation. Out of the presented methods an algorithm based on a continuous wavelet transform is implemented. Detection and delineation algorithm is tested on CSE standard signal database towards references determined both manually and automatically. Obtained results are compared to other congenerous methods. The diploma thesis is further concerned with an algorithm modification for experimental electrocardiograms of isolated rabbit hearts. Recording specifics of these data are introduced. Additionally, based on time and frequency analysis, particular modifications of the algorithm are proposed and realized. Due to a large extent of records functionality is verified on randomly selected database samples. Efficiency of the modified algorithm is evaluated through manually annotated references.

This paper discusses the possible use of Hilbert-Huang transform to analyze the data obtained from physical experiments. Specifically for the analysis of acoustic emission in the form of acoustic shock. The introductory section explains the concept of acoustic emission and its detection process. Subsequently are discussed methods for signal analysis in time-frequency domain. Specifically, short-term Fourier transform, Wavelet transform, Hilbert transform and Hilbert-Huang transform. The final part contains the proposed method for measuring the performance and accuracy of different approaches.

This master's thesis deals with the optimization of numerical coefficients of the Wiener filter for muscle noise filtering in ECG signals. The theoretical part deals with ECG signal characteristic and muscle interference. It also contains a summary of the wavelet transform, wavelet Wiener's filtration, methods for calculating of the threshold and thresholding. In the last theoretical part the characteristic optimization techniques, the exhausive search and Nelder-Mead simplex method are mentioned, which were implemented in the practical part of this thesis in MATLAB. The functional verification and Wiener's filter optimization were tested on the standard electrocardiograms database CSE. By using the methods of exhausive search, the initial estimate for the solution method Nelder-Mead was obtained. The optimization method Nelder-Mead gives better results in the orders of hundredths or tenths than the method of exhausive search. The practical part is finished by the comparison of results of implemented algorithm with optimum coefficients, implemented in this thesis, with the results of other methods for filtering muscle interference in ECG signals.

The thesis is focused on the study of detection of QRS complex in time a frequency domain. The aim is to implement selected methods and their comparison to assess the effectiveness of QRS complex.

Dissertation thesis is focused on real digital signal processing by quadrature mirror digital filter banks. In the first part a dual channel quadrature mirror digital filter bank is described briefly. Mainly transfer functions for distorted subband signals are described. In the next part generalized sigma-delta modulator and its linear model are described. Subsequently the generalized sigma-delta modulator is used in decomposition part of quadrature mirror digital filter bank. Designed structure is analyzed. Two design method of transfer functions are designed for the structure on the basis of analysis results. The first method is suitable for hand-made design by intuitive distribution of zeros and poles. The second method is more suitable for computer design. It is iterative method based on correlation. Transfer functions for quadrature mirror digital filter bank with sigma-delta modulators design examples are also part of thesis. Application of designed structure of quadrature mirror digital filter bank can lead to bigger compression ration in lossy data compression.