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ECG Signal Compression Based on Wavelet Transform
Ondra, Josef ; Hrubeš, Jan (referee) ; Kozumplík, Jiří (advisor)
Signal compression is daily-used tool for memory capacities reduction and for fast data communication. Methods based on wavelet transform seem to be very effective nowadays. Signal decomposition with a suitable bank filters following with coefficients quantization represents one of the available technique. After packing quantized coefficients into one sequence, run length coding together with Huffman coding are implemented. This thesis focuses on compression effectiveness for the different wavelet transform and quantization settings.
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Time-frequency analysis of electrograms
Doležal, Petr ; Ronzhina, Marina (referee) ; Kolářová, Jana (advisor)
This thesis deals with time-frequency analysis of electrograms measured on isolated guinea pig hearts perfused according to Langendorff. Time-frequency analysis is based on algorithms Matching Pursuit and Wigner-Ville Distribution. The theoretical part describes the basics of electrocardiography, measurement on isolated hearts, the theory of approximation method Matching Pursuit and its combination with the Wigner-Ville distribution spectrum showing the energy density of the signal. Also other common approaches of time-frequency analysis are presented including the theory of continuous wavelet transform. The presented algorithms were tested on a set of electrograms, on which were induced ischemia within measurement followed by reperfusion. The proposed method allows for the fast detection of ischemia without any a priori knowledge of the signal, and also serves as a tool for measurement of EG important points and intervals. In the conclusion efficacy of the method was presented and its possible uses has been discussed.
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Time-Frequency Signal Analysis
Kovačev, Radovan ; Polok, Lukáš (referee) ; Bařina, David (advisor)
The main subject of this work represents the time-frequency signal analysis. Firstly, it intends to provide the most essential theoretical background with focus on the continuous wavelet transform, where also a comparison of the key features with its close relative the short-time Fourier transform is performed. Afterwards, there follows a demonstration of the purpose with a practical example. The particular aim is to create a phase vocoder solution for modifying the length of a sound record duration and pitch shifting. Here, in this place, the functional principles, design, procedure of assembling, outputs and achieved results are well documented.
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ECG signal filtering in the wavelet domain
Zedníček, Vlastimil ; Vítek, Martin (referee) ; Smital, Lukáš (advisor)
The aim of this work is introduction with the method of filtering the signal using wavelet transform. Our task was to use a redundant wavelet transform for filtering ECG signals. First we met with wavelet filtering. In the practical part, we implemented a filter based on redundant DTWT in Matlab. The results were evaluated based on the achieved signal / noise ratio. The proposed filter, we tested the CSE database, and we tried to optimize the filter parameters and the degree of decomposition of wavelet transform, the bank decomposition and reconstruction filters, thresholding methods and threshold setting. The results were evaluated based on the achieved signal / noise ratio. as a last resort, we compared the results obtained with the results of different filtering methods
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ECG Signal Wavelet Filtering
Zahradník, Radek ; Kozumplík, Jiří (referee) ; Smital, Lukáš (advisor)
The aim of this work is introduction to problems about the wavelet transform and then to use this transformation to filter ECG signal disturbed with myopotentials. The first part of this thesis contains basic information about the measurement, waveform and disturbance of ECG signal. The next part describes the method of wavelet transform and its use for the signal filtering The last part describes the practical part of work, where the results of filtering with different filter settings are evaluated, especially the various types of thresholding. At the end of this part is a comparison of results from wavelet and linear filter.
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Identifikace finančních cyklů v eurozóně
Šmídová, Petra
Šmídová, P. Identification of financial cycles in euro area. Diploma thesis. Brno: Mendel University, 2023. This diploma thesis examines financial cycles in euro area countries using wavelet analysis. This method has significant advantages compared to the methods presented in the theoretical part of the thesis. The wavelet analysis allows to investigate both the time and the frequency domain at the same time and does not work with the assumption of the frequencies in which the financial cycle should be located. Credit and house prices were used as indicators of financial cycles. Statistically significant cycles in credit and house prices for individual euro area countries were identified in a Continuous Wavelet Transform. In the second section of the empirical part, a Wavelet Coherence Analysis was performed in order to answer the question whether financial cycles in the euro area are synchronised. Based on the results obtained, recommendations for macroprudential policy makers were made
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Vliv sentimentu na kryptoměnové trhy
Maňoušek, David
This paper empirically identifies the relationship between sentiment and cryptocurrency profitability. The analysis uses daily data for the five largest cryptocurrencies by market capi-talisation: bitcoin, ethereum, binance coin, ripple, and cardano. The sentiment variable used in the analysis is the Fear & Greed Index, which is a quantified measure of market fear and greed. We use wavelet coherence as the main method of the paper to determine the relationship between sentiment and cryptocurrency returns. All cryptocurrencies analysed have a positive correlation for investment horizons ranging from 4 to 32 days, with the sentiment variable as the leading indicator. For traders belonging to the group investing in cryptocurrencies for time frames of 4 to 32 days, the Fear & Greed Index can be used as an indicator to optimise trade entry. If the Fear & Greed Index is rising, investors can expect an increase in returns over a 4 to 32 day horizon and open a long position in response to the move, profiting from the move. The recommendation also applies with the opposite sign: if the Fear & Greed Index falls, investors can speculate on a fall in returns. For longer investment horizons, the Fear & Greed Index acts as a lagging indicator and should not be used to predict future market movements.
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Detection of gunshots from small arms
Nesvadba, Ondřej ; Malucha, Jan (referee) ; Sigmund, Milan (advisor)
This thesis deals with acoustical gunshot detection from small arms, typically of the calibre up to 10 mm, primarily in urban areas. Thesis includes initial research of methods, which are usually used for gunshot detection. The key part of this work is examination of typical values of gunshot signal. Based on the values obtained, decisive parameters in time and frequency domains are determined and detection algorithms are proposed. Function of these algorithms is tested and evaluated. The possible influence of various features of recordings on detection success rate was discussed.
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Respiratory Rate Estimation From Ecg And Ppg Signals Via Continuouswavelet Transfor
Sikorova, Pavlina
In this paper, a novel approach to estimate the respiratory rate from ECG and PPG signalsis proposed. The respiration signal is extracted from both signals using the continuous wavelettransform and the rate is estimated in time as well as frequency domain. Subsequent fusion of differentapproaches provides the result more robust. Designed algorithm predicts the breathing frequencywith the mean absolute error of 0.96 breaths per minute.
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