|
|
OpenCPU system usage in data processing
Yerpeissov, Serik ; Galáž, Zoltán (referee) ; Mžourek, Zdeněk (advisor)
Bachelor thesis deals with the OpenCPU system usage in data processing. The work is divided into theoretical introduction which contains a description of data processing in information and communication technologies, task and purpose of data processing, possibilities and practical usage of OpenCPU, practical usage and models of R, then the HTTP protocol and virtualization systems. Furthermore, the work deals with the realization of a sensor in OpenCPU environment through the PHP, HTML
|
|
|
Statistic Characteristic Function and its Usage for Digital Signal Processing
Mžourek, Zdeněk ; Mekyska, Jiří (referee) ; Smékal, Zdeněk (advisor)
Aim of this thesis is provide basic information about characteristic function used in statistic and compare its properties with the Fourier transform used in engineering applications. First part of this thesis is theoretical, there are discussed basic concepts, their properties and mutual relations. The second part is devoted to some possible applications, for example normality testing of data or utilization of the characteristic function in independent component analysis. The first chapter describes the introduction to probability theory for the unification of terminology and mentioned concepts will be used to demonstrate the interesting properties of characteristic function. The second chapter describes the Fourier transform, definition of characteristic function and their comparison. The second part of this text is devoted to applications the empirical characteristic function is analyzed as an estimate of the characteristic function of examined data. As an example of application is describe a simple test of normality. The last part deals with more advanced applications of characteristic function for methods such as independent component analysis.
|
|
|
Application of statistical analysis of speech in patients with Parkinson's disease
Bijota, Jan ; Mžourek, Zdeněk (referee) ; Galáž, Zoltán (advisor)
This thesis deals with speech analysis of people who suffer from Parkinson’s disease. Purpose of this thesis is to obtain statistical sample of speech parameters which helps to determine if examined person is suffering from Parkinson’s disease. Statistical sample is based on hypokinetic dysarthria detection. For speech signal pre-processing DC-offset removal and pre-emphasis are used. The next step is to divide signal into frames. Phonation parameters, MFCC and PLP coefficients are used for characterization of framed speech signal. After parametrization the speech signal can be analyzed by statistical methods. For statistical analysis in this thesis Spearman’s and Pearson’s correlation coefficients, mutual information, Mann-Whitney U test and Student’s t-test are used. The thesis results are the groups of speech parameters for individual long czech vowels which are the best indicator of the difference between healthy person and patient suffering from Parkinson’s disease. These result can be helpful in medical diagnosis of a patient.
|
|
|
Entropic models of data traffic
Blažek, Petr ; Mžourek, Zdeněk (referee) ; Slavíček, Karel (advisor)
This thesis solves possibility of using entropy for anomaly detection in data communication and especially for security attacks. The main advantage of using entropy is ability to identify unknown attacks because entropy detects changes in network traffic but not the content as existing methods. In this work was tested the suitability of different models entropy (Shannon, Renyi, Tsallis). Also been tested the effect of Renyi and Tsallis parameter on resulting entropy. From the resulting values, I found that all tested entropy achieve good result in the identification of anomalies in network traffic.
|
|
|
Signal Decomposition using EMD transform
Mžourek, Zdeněk ; Mekyska, Jiří (referee) ; Smékal, Zdeněk (advisor)
Aim of this thesis is to introduce empiric mode decomposition as a method for decomposing arbitrarily nonlinear and non-stationary signal into intrinsic mode functions. Using empiric modal decomposition together with Hilbert transform produces instantaneous frequency. We can use this instatenous frequency to create a Hilbert spectrum and use it for analysis in time-frequency domain. In next part we show several drawbacks of this method. We also present several ways how to improve empirical mode decomposition algorithm to obtain better results. An example of decomposition by empiric mode decompositon is made to illustrate how the whole procedure works.
|
|
|
Cluster analysis in the field of pathological speech signal processing
Čapek, Karel ; Mžourek, Zdeněk (referee) ; Galáž, Zoltán (advisor)
The bachelor thesis deals with the calculation of speech features that quantifies the degradation of speech production caused by the presence of certain speech pathology and the subsequent clasification of considered speech pathologies into several groups using the k-means algorithm. The purpose was to find the groups of pathologies that in spite of possible differences in the origin do affect phonation and articulation skills of the speakers and damage the quality of speech. The work uses the phonation of vowels "a" speech task as the most commonly used speech task in the field of pathological speech processing, because of its resistance to demographic and linguistic characteristics of the speakers. Furthermore, the preliminary analysis was applied to the featuresin order to select the features to best characterize the degradation of speech production. Finally, the selected features were used to find the resulting groups of pathologies using k-means algorithm.
|
|
|
Visualization of multidimensional data using web technologies
Burian, Vojtěch ; Galáž, Zoltán (referee) ; Mžourek, Zdeněk (advisor)
Scope of this work is the problematic of data visualization. Data visualization is a useful tool to present and gather new information and thus get to better decisions. In theoretical part, data analysis topics are dealt with. Then specific types of graphs are listed and explained, and in next part problems with graph creation are pinpointed. Basics of graphic and web design are also mentioned. Practical part is focused on visualization of data of processed results of speech analysis, gathered from patients with Parkinson disease. Because majority of people in medical industry do not have, or is not able to work with specialized software (such as Matlab), outputs in HTML table and SVG format were created based on Python programming language. Both these parts are accommodated into webpage, which can be easily opened in web browser installed in most of computers regardless of operation system used.
|
|
|
Signal processing using parallel mathematical operations
Polášek, Jaromír ; Ležák, Petr (referee) ; Mžourek, Zdeněk (advisor)
This Bachelor thesis deals with the acceleration of function calculations, using parallel computing mediated by NVDIA graphics cards via CUDA technology. The theoretical part describes the general principles of parallel computing and the basic characteristics and parameters of graphics cards NVDIA. The theoretical part also deals with basic principles of CUDA technology. End of the theoretical part focuses on FFTW and cuFFT libraries. The practical part deals with the comparison of the performance between GPU and CPU functions filter2D and Canny and practical possibilities of accelerating fast convolution calculation. The practical part also describes sample code that was used to compare the performance between GPU and CPU. The results of this program are then plotted and evaluated.
|
|
|
OpenCPU system usage in data processing
Yerpeissov, Serik ; Galáž, Zoltán (referee) ; Mžourek, Zdeněk (advisor)
Bachelor thesis deals with the OpenCPU system usage in data processing. The work is divided into theoretical introduction which contains a description of data processing in information and communication technologies, task and purpose of data processing, possibilities and practical usage of OpenCPU, practical usage and models of R, then the HTTP protocol and virtualization systems. Furthermore, the work deals with the realization of a sensor in OpenCPU environment through the PHP, HTML
|
|
|
Signal processing using parallel mathematical operations
Polášek, Jaromír ; Ležák, Petr (referee) ; Mžourek, Zdeněk (advisor)
This Bachelor thesis deals with the acceleration of function calculations, using parallel computing mediated by NVDIA graphics cards via CUDA technology. The theoretical part describes the general principles of parallel computing and the basic characteristics and parameters of graphics cards NVDIA. The theoretical part also deals with basic principles of CUDA technology. End of the theoretical part focuses on FFTW and cuFFT libraries. The practical part deals with the comparison of the performance between GPU and CPU functions filter2D and Canny and practical possibilities of accelerating fast convolution calculation. The practical part also describes sample code that was used to compare the performance between GPU and CPU. The results of this program are then plotted and evaluated.
|
guest ::
RSS feed.