Sökning: "Multitaper"
Visar resultat 1 - 5 av 16 uppsatser innehållade ordet Multitaper.
1. Estimation of respiratory frequency from Heart Rate Variability
Master-uppsats, Lunds universitet/Matematisk statistikSammanfattning : In this master's thesis the ability to estimate the respiratory frequency from heart rate variability measurement is analyzed. The goal was to implement a solution that is easily transferable to real time. LÄS MER
2. Optimal Multitaper Spectrograms
Master-uppsats, Lunds universitet/Matematisk statistikSammanfattning : Multitaper spectrograms have been proposed as a method of improving the spectrogram as a time-frequency representation (TFR). This thesis aimed to investigate both previously used and new methods for combining multitaper spectrograms of a Gaussian signal and a chirp. LÄS MER
3. Estimating the risk of insurance fraud based on tonal analysis
Master-uppsats, Lunds universitet/Matematisk statistikSammanfattning : Insurance companies utilize various methods for identifying claims that are of potential fraudulent nature. With the ever progressing field of artificial intelligence and machine learning models, great interest can be found within the industry to evaluate the use of new methods that may arise as a result of new advanced models in combination with the rich data that is being gathered. LÄS MER
4. Classifying Heart Rate Variability Data using Multitaper Spectrum Analysis
Kandidat-uppsats, Lunds universitet/Matematisk statistikSammanfattning : Heart rate variability (HRV) is the variation between two consecutive heartbeats. The irregular variability in this interval can indicate different health issues such as stress. The goal of this project is to correctly classify if a HRV signal comes from a resting state or a state which is affected by stress related stimuli. LÄS MER
5. Multitaper analysis of HRV power and its stress-related correlation to respiration frequency
Master-uppsats, Lunds universitet/Matematisk statistikSammanfattning : In this Master thesis, different multitaper methods are implemented to estimate the spectra of respiratory signals and HRV data, and further to estimate the correlation between the respiratory center frequency and the narrow-banded high frequency band of HRV power. The methods are applied first on ARMA-process data, then on the integrated pulse frequency modulation (IPFM) data simulations, where the evaluation is performed by calculating the bias and standard deviation of the narrow-banded HRV power and its correlation with respiratory frequency. LÄS MER