Scale-temporal transformations of biomedical non-stationary signals
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Дата
2025
Науковий керівник
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Видавець
Igor Sikorsky Kyiv Polytechnic Institute
Анотація
In this work, the analysis of families of wavelet transform wave functions was carried out for their use in the problem of isolating a non-stationary trend of a biomedical signal. Modeling of measured signals with simple trends with noise and interference is performed. Wavelet decomposition and trend highlighting of signals was carried out using the families of Dobeshi, Haar, Simlet, Koiflets.
Measuring signals with non-stationary trends and random interference were formed, for which were selected wavelet functions for a different number of decomposition levels and the error of trend selection was estimated. The analysis of the effectiveness of using different wavelet functions to isolate a complex trend of biomedical signal was performed.
The object of research is the process of isolating informative components from noise-shaped signals in the biomedical tasks of control and monitoring.
The subject of the study is methods and algorithms for identifying trends of biomedical signal.
Scientific novelty:
1. The use of wavelet decomposition to non-stationary trend of a noise-like signal is proposed and substantiated.
2. The evaluation completed of the standard error of the selection of a non-stationary trend on the type of wave function.
Practical value of the results – to restore the lost trajectory of a moving biological object in conditions of its complex movement in adaptive control systems and case of sudden changes in trajectory moving, when changing the output signals of sensors in control systems.
Опис
Ключові слова
wavelet transforms, biomedical signals, non-stationary trend, control systems, biomedical sensors
Бібліографічний опис
Hussin Ibrahim Ramadan Ibrahim. Scale-temporal transformations of biomedical non-stationary signals : Master's Thesis : 163 Biomedical engineering / Hussin Ibrahim Ramadan Ibrahim. - Kyiv, 2025. -134 p.