An advanced signal processing technique, higher-order spectra, is proposed to in vestigate the nonlinear coupling phenomena of the heart sounds. To extract more higher-order information of the heart sounds, a non-Gaus...An advanced signal processing technique, higher-order spectra, is proposed to in vestigate the nonlinear coupling phenomena of the heart sounds. To extract more higher-order information of the heart sounds, a non-Gaussian AR model is selected for parametric bispectral estimation in analyzing several kinds of heart sounds. The non-Gaussian AR model of the sound signals is llsed to detect quadratic nonlinear interactions and to classify two patterns of heart sounds in terms of the parametric bispectral estimate. The bispectral cross-correlation is employed to the order determination of the model. Several real heart sound data are imple mented to show that the quadratic nonlinearity exist in both normal and clinical heart sounds.It was found that bispectral techniques are effective and useful tools in analyzing heart sounds and other acoustical signals展开更多
文摘An advanced signal processing technique, higher-order spectra, is proposed to in vestigate the nonlinear coupling phenomena of the heart sounds. To extract more higher-order information of the heart sounds, a non-Gaussian AR model is selected for parametric bispectral estimation in analyzing several kinds of heart sounds. The non-Gaussian AR model of the sound signals is llsed to detect quadratic nonlinear interactions and to classify two patterns of heart sounds in terms of the parametric bispectral estimate. The bispectral cross-correlation is employed to the order determination of the model. Several real heart sound data are imple mented to show that the quadratic nonlinearity exist in both normal and clinical heart sounds.It was found that bispectral techniques are effective and useful tools in analyzing heart sounds and other acoustical signals
