Ph.D. Tezi Görüntüleme | |||||||||||||||||||||
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| Summary: and can be processed with analog or digital signal processing techniques. These processed signals serve as an excellent tool for heart diseases analysis. Most important property of using skin electrodes is that it is a non-invasive technique, meaning that this signal can be measured without entering the body at all. Despite this facility, non-invasive methods include problems such as mixing with other physiological signals and noise. In this thesis, the purpose is to determine the appropriate algorithms for fetal electrocardiogram extraction by means of blind source separation algorithms and find a new blind source separation algorithm. As the first step, artificially generated electrocardiogram signals were mixed and used to find suitable algorithms. Three main algorithms of blind source separation; FastICA, JADE, non-parametric ICA, and new non-parametric ICA algorithms compared for this purpose. The results obtained indicate that non-parametric algorithms can be employed to preprocess electrocardiogram signals to separate the effects of maternal electrocardiogram signal and interference signals. Key Words: Independent Component Analysis, Blind Source Separation, Electrocardiogram, Entropy, Tsallis Entropy, Shannon Entropi, Information Theory, Relative Entropy | |||||||||||||||||||||