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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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Acoustical simulation of going car
Lacko, Tomáš ; Horka, Michal (referee) ; Sigmund, Milan (advisor)
This project includes an overview of different processing methods phonograms. It focuses primarily on time - frequency analysis carried out using Fast Fourier Transform (STFT). The main essence is to evaluate the time - frequency analysis of recorded motor vehicle, driving at different options, together with an analysis of driver activity in these variants. Based on the results of the analysis deals with the creation of synthetic audio signals of motor vehicle records. Further addresses the creation of the program for acoustic simulation engine is running smoothly when driving a car. Processing recorded signals and their evaluation is transferred using Matlab 7.7.0 ( R2008 )
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Time Frequency Analysis of ERP Signals
Bartůšek, Jan ; Provazník, Ivo (referee) ; Černocký, Jan (advisor)
Tato práce se zabývá vylepšením algoritmu pro sdružování (clustering) ERP signálů pomocí analýzy časových a prostorových vlastností pseudo-signálů získaných za pomocí metody analýzy nezávislých komponent (Independent Component Analysis). Naším zájmem je nalezení nových vlastností, které by zlepšily stávající výsledky. Tato práce se zabývá použitím Fourierovy transformace (Fourier Transform), FIR filtru a krátkodobé Fourierovy transformace ke zkvalitnění informace pro sdružovací algoritmy. Princip a použitelnost metody jsou popsány a demonstrovány ukázkovým algoritmem. Výsledky ukázaly, že pomocí dané metody je možné získat ze vstupních dat zajímavé informace, které mohou být úspěšně použity ke zlepšení výsledků.
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Methods for electroencephalogram records comparison
Mikešová, Tereza ; Ronzhina, Marina (referee) ; Janoušek, Oto (advisor)
This bachelor thesis starts with a theoretical section that explores the methods of electroencephalographic records analysis. The chosen methods are suitable for signal comparison. One of the methods, specifically STFT, is subsequently used in the practical segment. The aim of the practical section is to verify the ability of the proposed method to distinguish between the signals from two groups. For these purposes, rest and mental load records are used, the load being induced by counting mathematical examples. Of the examined power parameters, the differences in the ratio of beta and alfa band power and the relative power of alfa band showed the greatest statistical significance. The most appropriate setup of STFT seems to be with the shortest time window of 2 seconds.
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The analysis of the clarinet spectrum from different manufacturers
Suchánek, Tomáš ; Mojdl, Edgar (referee) ; Jirásek, Ondřej (advisor)
Bachelor’s thesis focuses on spectral analysis of six B clarinets made by manufacturers Buffet Crampon, RZ Woodwind Manufacturing and Yamaha. Instruments were tested by two professional musicians with different timbral preferences and the resulting spectrum is then applied to how psychoacoustic measurements define timbre perception. Furthermore, the impact of different dynamics or reeds is discussed and significant part of analysis also describes directivity patterns of individual higher harmonics or characteristic formant areas.
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Analysis of sleep EEG signal
Ježek, Martin ; Kozumplík, Jiří (referee) ; Rozman, Jiří (advisor)
Cílem této práce byl vývoj programu pro automatickou detekci arousalu v signálu spánkového EEG s použitím metod časově-frekvenční analýzy. Předmětem studie bylo 13 celonočních polysomnografických nahrávek (čtyři svody EEG, EMG, EKG a EOG), tj. celkově více než 100 hodin záznamu. Jednalo se o část dat z dřívějších výzkumných prací expertní lékařky v problematice spánku Dr. Emilie Sforzy, Ženeva, Švýcarsko, která rovněž poskytla základní hodnocení těchto dat. V záznamech bylo celkem označeno 1551 arousal událostí. Pro usnadnění výběru konkrétní metody časově-frekvenční analýzy byla následně vytvořena sada nástrojů pro vizualizaci jednotlivých signálů a jejich různých časově-frekvenčních vyjádření. S ohledem na závěry vizuální analýzy, charakter signálu EEG a efektivitu výpočetních metod byla pro analýzu vybrána waveletová transformace s mateřskou vlnkou Daubechies řádu 6. Jednotlivé svody EEG byly dekomponovány do šesti frekvenčních pásem. Z takto odvozených signálů a signálu EMG byly následně stanoveny ukazatele možné přítomnosti události arousalu. Tyto ukazatele byly dále váhovány lineárním klasifikátorem, jehož hodnoty vah byly optimalizovány pomocí genetického algoritmu. Na základě hodnoty lineárního klasifikátoru bylo rozhodnuto o přítomnosti události arousalu v daném svodě EEG – arousal byl detekován, jestliže hodnota klasifikátoru překročila danou mez na dobu více než 3 a méně než 30 vteřin. V celém záznamu pak byl arousal označen, byl-li detekován alespoň v jednom ze svodů EEG. Následně byly odvozeny míry senzitivity a selektivity detekce, jež byly rovněž základem pro stanovení fitness funkce genetického algoritmu. Pro učení genetického algoritmu byly vybrány první čtyři záznamy. Na základě takto optimalizovaných vah vznikl program pro automatickou detekci, který na celém souboru 13 záznamů dosáhl ve srovnání s expertním hodnocením míry senzitivity 76,09%, selektivity 53,26% a specificity 97,66%.
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Visualization of sound fields
Kovář, Petr ; Klusáček, Stanislav (referee) ; Havránek, Zdeněk (advisor)
This bachelor's thesis deals with problems of acoustical field visualization using near-field acoustical holography. This method is often refered as NAH. Within the thesis the basic acoustical field variables are processed and described. Two algorithms were analysed, namely the Statistically Optimal Algorithm (SONAH) and the Iterative Algorithm using the Fourier Transform (STFT) with a K-filter (Wave-Domain Filter). These algorithms are described in detail. The outcome of the practical part of this thesis is the application for sound pressure visualization. The application is created in the LabVIEW environment from the known codes and the calculation of the sound pressure is performed with one of the two algorithms described in this thesis. From depicted acoustical maps the disadvantages of this method and differences between algorithm are shown. These algorithms are then compared according to speed of the calculation.
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Music Source Separation
Holík, Viliam ; Veselý, Karel (referee) ; Mošner, Ladislav (advisor)
Neural networks are used for the problem of music source separation from recordings. One such network is Conv-TasNet. The aim of the work is to experiment with the already existing implementation of this network for the purpose of potential improvement. The models were trained on the MUSDB18 dataset. It was successively experimented with the change of the network structure, transforming signals from the time domain to the frequency domain for the purpose of calculating the loss function, replacing different loss functions with the original one, finding the optimal learning rate for each loss function and gradually decreasing the learning rate during the learning process. The best experiments according to the SDR metric were training with loss functions L1 and logarithmic L2 in the time domain with a higher initial learning rate with its gradual decrease during the learning process. In a relative comparison of the best models to the baseline, it is more than 2.5% improvement.
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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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Methods for electroencephalogram records comparison
Mikešová, Tereza ; Ronzhina, Marina (referee) ; Janoušek, Oto (advisor)
This bachelor thesis starts with a theoretical section that explores the methods of electroencephalographic records analysis. The chosen methods are suitable for signal comparison. One of the methods, specifically STFT, is subsequently used in the practical segment. The aim of the practical section is to verify the ability of the proposed method to distinguish between the signals from two groups. For these purposes, rest and mental load records are used, the load being induced by counting mathematical examples. Of the examined power parameters, the differences in the ratio of beta and alfa band power and the relative power of alfa band showed the greatest statistical significance. The most appropriate setup of STFT seems to be with the shortest time window of 2 seconds.
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