期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2014
卷号：5
期号：1
DOI：10.14569/IJACSA.2014.050104
出版社：Science and Information Society (SAI)
摘要：Classification of heart sound signals to normal or their classes of disease are very important in screening and diagnosis system since various applications and devices that fulfilling this purpose are rapidly design and developed these days. This paper states and alternative method in improving classification accuracy of heart sound signals. Standard and improvised Multi-Layer Perceptron (MLP) network in hierarchical form were used to obtain the best classification results. Two data sets of normal and four abnormal heart sound signals from heart valve diseases were used to train and test the MLP networks. It is found that hierarchical MLP network could significantly increase the classification accuracy to 100% compared to standard MLP network with accuracy of 85.71% only.
