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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.
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Analysis and comparison of ROC curves of audio signals
Pospíšil, Lukáš ; Staněk, Miroslav (referee) ; Poměnková, Jitka (advisor)
This thesis deals with oportunity of ROC curve usage in the description of methods that work with sound signals. Specifically, it focuses on ways of detecting of stress in speech signals. The detection itselfs is done in a range of frequencies of the sound signal. There is also a classifier designed using ROC curves that decides whether the input signal is stressed or not. The output of this thesis are findings gathered from analyses and also some recommendation based on those analyses.
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Estimation and analysis of speech signal periodicity
Malucha, Jan ; Poměnková, Jitka (referee) ; Sigmund, Milan (advisor)
Theoretical part starts with a short introduction to speech signals and short time analysis method. Concept of periodicity is clarified. This is followed by analysis of the speech signal parameters - voiced/unvoiced classification, intonation and short time period similarity. Next the overview of methods used to analyze the mentioned parameters together with concepts of their algorithms is provided. These methods include ZCR, STE, HNR, ACF, NCC, AMDF and DTW. Algorithms using the methods with supporting preprocessing algorithms were programmed in MATLAB for practical part. All were tested on real speech signals and the results are discussed at the end of the thesis.
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Analysis of spectral characteristics of signals
Sedláček, Matyáš ; Klejmová, Eva (referee) ; Poměnková, Jitka (advisor)
The subject of this bachelor’s thesis are the properties of power spectral density estimates, mainly how their properties depend on the analyzed signal’s parameters and the method being used. Important signal properties from the perspective of spectral analysis are defined, as well as measures for judging the estimate. Based on those, a choice of nonparametric and parametric spectral estimation methods is described. Analysis is performed on simulated signals and the results generalized into a set of recommendations for finding an estimate via an optimal method. These recommendations are then scrutinized and further discussed through estimation of real signal PSDs. Included is an application in MATLAB App Designer for generating spectral estimates and a collection of signals used.
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Warning system to keep the vehicle in the lane
Fendrich, Vítězslav ; Říha, Kamil (referee) ; Poměnková, Jitka (advisor)
This thesis adresses designing a device that detects lane departure of a vehicle via a video feed from a camera module. This device is intended to be attached onto the windshield of the vehicle. The initial part of the thesis will cover the current methods of lane departure detection through a video feed. In the following part the selection of suitable hardware, specifically the latest model of a Raspberry Pi, has been made. Afterwards a suitable container for the aforementioned hardware has been designed and created using a 3D printer. Subsequently an appropriate LDWS algorithm is chosen and designed. In the next part, the range and parameters of a testing database through which the proper functionality of the device will be tested on are chosen. The final part of the thesis contains evaluation of the success rate of detection via the acquired database.
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Identification of significant spectral components in speach signal in stress
Dulesov, Egor ; Tučková, Jana (referee) ; Poměnková, Jitka (advisor)
The aim of this master’s thesis is to learn the problem of analysis and identification of significant spectral components in speech signal. Based on learning a special literature chooses the suitable methods of spectrum estimate. Does learning the literature in specification of testing of spectral components significate. Makes a procedure for identification of chosen speech formants. Does this procedure for audio signals both of in stress and in normal state. Estimates the results, compares efficiency of chosen methods and determine threshold for chosen formant of analyzed stress signal. States the recommendations for speech spectral analysis in stress situation.
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Face Recognition in Security and Surveillance Camera Systems
Malach, Tobiáš ; Říha, Kamil (referee) ; Hudec,, Róbert (referee) ; Poměnková, Jitka (advisor)
Tato práce se zabývá zvýšením úspěšnosti rozpoznávání obličejů v dohledových CCTV systémech a systémech kontroly vstupu. K dosažení tohoto cíle je využit nový přístup - optimalizace vzorů obličejů. Optimalizace tvorby vzorů umožní vytvořit vzory, které zajistí zvýšení úspěšnosti rozpoznání. Měření a další zvyšování úspěšnosti rozpoznávání obličejů vyžaduje naplnění následujících dílčích cílů této práce. Prvním cílem je návrh a sestavení reprezentativní databáze obličejů, která umožní dosáhnout věrohodných a statisticky spolehlivých výsledků rozpoznávání obličejů v dohledových CCTV systémech a systémech kontroly vstupu. Druhým cílem je vytvoření metodiky pro statisticky spolehlivé porovnání výsledků, která umožní konstatování relevantních závěrů. Třetím cílem je výzkum tvorby vzorů a jejich optimalizace. Z dosažených výsledků vyplývá, že optimalizace tvorby vzorů zvyšuje úspěšnost rozpoznávání v uvedených a náročných aplikacích typicky o 4-8%, a v některých případech i 15%. Optimalizace tvorby vzorů přispívá použitelnosti rozpoznávání obličejů v uvedených aplikacích.
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Evaluation of classification efficiency using ROC cruves
Dluhý, Vojtěch ; Sigmund, Milan (referee) ; Poměnková, Jitka (advisor)
This semestral thesis is focused on work eith the ROC curves. Introduces the reader with ROC curves and their use to analyzing signals. Also shows an algorithm for detecting sound of siren in record using a simple algorithm and evaluation of various jamming sound of sirens by displaying the ROC curves, supplemented by calculation and comparing the areas under these curves (AUC). The algorithm is written in a development enviroment Matlab.
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Filtration of time series
Pinkava, Jan ; Poměnková, Jitka (referee) ; Maršálek, Roman (advisor)
Thesis is aimed at describing the concepts and basic principles in the economy in gross domestic product. Furthermore it deals with the description of time series, their types, characteristics and the basic classification. A decomposition of time series into thein components is indicated. Another part is a basic description of the most commonly used economic filters - Hodrick-Prescott and Baxter-King. The Christiano-Fitzgerald and frequency-selective filter for short length time series have been practically implemented in MATLAB. The rest of the thesis deals with the application of above mentioned filters to data of Czech Republic, European Union, USA and selected EU countries. Moreover, the correlation between spectral components of the data for selected countries is investigated. KEYWORDS
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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.
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