National Repository of Grey Literature 119 records found  1 - 10nextend  jump to record: Search took 0.01 seconds. 
Boundary effects in signal processing: From classical problems to new opportunities
Popoola, Seyi James ; Druckmüllerová, Hana (referee) ; Cicone, Antonio (advisor)
Tato práce se zaměřuje na hraniční problémy při rozkladu signálů. Problematika hranic klasických metod byla rozsáhle studována, ale v posledních několika desetiletích byla představena nová generace metod. Implementace těchto nových metod má potenciál produkovat efektivním způsobem přesnější, flexibilnější a interpretovatelné výsledky, které mohou pomoci posunout výzkum v reálných aplikacích v různých oblastech. Hraniční problémy pro tyto techniky byly studovány teprve nedávno. Dosud zveřejněné výsledky ukazují, že tyto metody mají svá omezení a předpoklady, které je třeba pečlivě zvážit, aby se předešlo možnému zneužití. V této studii identifikujeme a řešíme hlavní překážky spojené s používáním těchto nových metod a poskytujeme také doporučení, jak je co nejefektivněji využít. Abychom dále ilustrovali možné důsledky nesprávného použití, provádíme komplexní zkoumání jejich aplikace na skutečná data a provádíme numerické simulace. Nakonec navrhujeme soubor osvědčených postupů pro optimalizaci výkonu těchto technik v kontextu rozkladu signálu. Zásadním návrhem je použít před aplikací jakékoli metody rozkladu techniku rozšíření signálu jako prostředek ke zmírnění hraničních efektů.
Automatic Retinal Image Quality Analysis
Dovbush, Andrii ; Rydlo, Štěpán (referee) ; Kavetskyi, Andrii (advisor)
The work was carried out in the context of the development of an autonomous ophthalmological examination centre. In addition to the accuracy of assessing image quality, a significant factor was the speed of calculation of key image quality parameters, which would allow real-time operation of the centre. Based on recent researches and scientific discoveries, there was a need of additional study on algorithms' time performance. The main goal of the work was to create an algorithm for assessing image quality, based on the best combination of image quality parameters in the context of effectiveness-to-time performance. This eventually led to the development of a tool for analysing retinal image quality features and the subsequent analysis of selected combinations of IQA algorithms and image channels. Two methods for selecting the best combinations of algorithms and image channels were chosen: the absolute performance method and the relative performance method. As a result, their weaknesses were found and a possible solution to these problems was proposed by using the best-coverage approach. Approximately 150 possible combinations of quality feature and channel extraction algorithms have been collected and analysed. Among the selected algorithms it was also possible to determine the algorithms dependent on the level of image noise and also the influence of resolution downscaling on the overall performance of the different algorithms for quality features. The effect of noise on the Sobel edge detector and the Canny edge detector was explained.
Digital Audio Steganography
Kabelka, Petr ; Malaník, Petr (referee) ; Strnadel, Josef (advisor)
The field of steganography deals with concealing information with the goal of hiding their very existence. The goal of this work is to create a summary of existing digital audio steganography methods and implement some of them. This work presents easily extensible and usable multiplatform library for audio steganography written in the Python programming language and a program that uses it. At the end of this work are the implemented methods compared against each other and against the published methods. Because it is hard to find concrete implementations of various published methods, the presented library enables almost anyone to easily use the implemented steganographic methods and to continue working on research in this field without the need to reimplement all of them.
Optimization of wavelet transform in the task of intracardiac ECG segmentation
Ředina, R.
My work deals with the selection of an appropriate wavelet transform setting for feature extraction from intracardiac ECG recordings. The studied signals were obtained during electrophysiological examinations at the Department of Pediatric Medicine, University Hospital Brno. In this paper, several wavelets are tested for feature extraction which is followed by adaptive thresholding to detect atrial activity from the extracted features. The procedure is evaluated using the F-score. Although the presented procedure does not appear to be overall effective for intracardiac signal segmentation, it certainly does not reject the use of wavelet transforms in combination with advanced machine learning, neural network, or deep learning techniques.
Selected Aspects of Statistical Significance Testing in Time-Frequency Analysis
Klejmová, Eva ; Kohl,, Zdeněk (referee) ; Fidrmuc, Jarko (referee) ; Poměnková, Jitka (advisor)
Přeložená dizertační práce se zabývá analýzou a posouzením kvality odhadu frekvenční a časově-frekvenční transformace dat a formulaci doporučení pro práci s metodami. Při použití těchto metod vyvstává otázka, jak vyhodnotit, které složky spektrogramu jsou statisticky významné a které nikoli. V této práci analyzujeme vlastnosti standardních testů statistické významnosti. Diskutujeme o jejich výhodách a nevýhodách s ohledem na heteroskedastický charakter dat. Na základě našich experimentů jsou v práci navrženy dva typy testovacích metod, které snižují negativní aspekty standardních testů. Práce jen zakončena vytvořením rámce pro filtrování dat pomocí námi navržených metod.
Analysis of time-frequency characteristics of signals
Vitouš, Jiří ; Ředina, Richard (referee) ; Poměnková, Jitka (advisor)
This thesis focuses on time-frequency analysis of discrete signals. The aim of this work is to compare the most well known methods for spectro/scalegram estimation. The two main topics discussed are: The compromise between time and frequency resolution and the effect of noise in input data on the quality of estimated spectrograms. To achieve this a database has been created. This database consists of real and artificial signals on which the analysis can be performed and evaluated. This database is used in created demonstration application. This application is also used in a created laboratory task.
Wavelet transform
Valter, Boris ; Hlávka, Zdeněk (advisor) ; Dvořák, Jiří (referee)
Wavelet transform is a term from signal analysis. It is mostly used in physics, but also in finance, where we can use it to find a trend in different financial data. In the first chapter we will describe two older methods of signal analysis: Fourier transform and short-time Fourier transform. In the second chapter we show, how wavelet transform works, derive frequently used algorithm for calculating discrete wavelet transform and at the end we show several practical examples. This thesis was considered to deepen the knowledge of time-frequency analysis of signals, for better understanding of the principle, how wavelet transform works, and for potential extending its use. Powered by TCPDF (www.tcpdf.org)
Automatic detection of microcalcifications in mammogram images
Hývlová, Denisa ; Jakubíček, Roman (referee) ; Harabiš, Vratislav (advisor)
This bachelor thesis is focused on detection of microcalcification in mammography images. The introduction describes connection between their presence and breast cancer, principle of mammography and the DICOM standard used in radiology. In the following part the methods used for microcalcification enhancement and segmentation are explained. Detection algorithm based on wavelet transform, morphological closing and thresholding was designed in MATLAB. For evaluation of the results a graphical user interface was developed and an algorithm for automatic evaluation of the success rate in annotated mammography database was implemented.
Liveness Detection on Touchless Fingerprint Scanner
Fořtová, Kateřina ; Kanich, Ondřej (referee) ; Heidari, Mona (advisor)
This Bachelor's Thesis is focused on liveness detection of fingerprints with using touchless sensor. Work summarizes theoretical introduction to biometrics, fingerprint processing and some of present researches for liveness detection. The new approach is introduced with using Local Binary Pattern algorithm, Sobel and Laplacian operator and Wavelet transform. Artificial Neural Networks, Support Vector Machines and Decision Trees were used for final classification. Several experiments with dataset illuminated by lights with various wavelengths were realized. It was discovered, that fingerprints illuminated by red light reached the best accuracy 90.1% compared to other considered wavelenghts of visible light. The classification with vector based on Local Binary Pattern achieved average accuracy 89.8%, accuracy with vector based on Sobel and Laplacian operator was 91.5%. Several Wavelet families were used for Wavelet transform during experiments. The best accuracy achieved wavelets of Biorthogonal spline wavelet family (85.1%) and wavelets from Reverse biorthogonal spline wavelet family (86.6%).
Finding The Fault Inception Time Using Wavelet Transform
Bukvisova, Zuzana
This paper deals with the transient detection method utilizing the wavelet transform, which proved to be more suitable for this purpose than the Fourier transform. The aim of this work is to analyze data, obtained from the power network model created in PSCAD software, and to determine the time of the fault inception. This calculated time is then compared with the actual fault inception time set in the model. The results show that the wavelet analysis can successfully detect all tested faults.

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