id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_njzbswnor5hvngpfyf2j222agy	Davut Hanbay	An expert system based on least square support vector machines for diagnosis of the valvular heart disease	2009	9	.pdf	application/pdf	6277	796	64	system based on least squares support vector machines (LS-SVM) for diagnosis of valvular heart disease Wavelet packet decomposition (WPD) and fast-Fourier transform (FFT) methods are realized to automatically classify Doppler signals using pattern recognition techniques (Chan, Chan, Lam, Lui, & Poon, 1997; Guler & Nevertheless, the effective studies on the Doppler heart sounds are also limited (Turkoglu, Arslan, basic properties of the pattern recognition, the Doppler heart signals, WPD, FFT, wavelet entropy and LS-SVM. implementation stage is described and the effectiveness of the proposed method for the classification of Doppler signals in the diagnosis of VHD is demonstrated. A representative example of the wavelet packet decomposition of the Doppler sound signal of the heart mitral The waveforms of terminal nodes (i = 1–256) of wavelet packet decomposition at eight-level of the DHS signal. In this paper, the application of the wavelet entropy to the feature extraction from DHS signals was shown.	./cache/work_njzbswnor5hvngpfyf2j222agy.pdf	./txt/work_njzbswnor5hvngpfyf2j222agy.txt