粗集神经网络系统及其应用

讨论了粗集神经网络系统及其在心电图自动识别中的应用。根据识别需要,从MIT心电图数据库获取心电图特征参数,根据粗集理论对属性进行优化,并用BP神经网络进行学习。运用这些特征参数和训练好的BP神经网络对心电图进行分类,识别准确率达到90%。

Rough Neural Network System and Its Application in Electrocardiogram Auto-recognition

In this paper, a rough neural network system is given and applied in Electrocardiogram auto-recognition. Based on medical requires, this paper has picked up the characteristic parameters of signals from Massachusettes Institute of Technology (database). According to Rough sets theory, the attributes are optimized and studied with BP neural network. In the end, the Electrocardiogram samples are classified with those characteristic parameters. The result shows that the right ratio goes to 90%. The experiment shows that the system has the advantages of fast computation and easy realization and the system is better than other methods in optimizing attributes and enhancing the right ratio of classification.