一种新的自适应数字滤波方法的研究

Research on self-adapting digital filter

自适应数字滤波中理想信号通常难于确定。针对这一问题,根据均方误差和高频信号的特征,将二者结合起来考虑,提出一种新的自适应数字滤波的方法。应用该方法在252组真实实验数据中进行相应的自适应滤波测试,并对滤波结果分别采用BP神经网络和支持向量机两种分类方法进行分类测试。实验结果表明,新方法具备良好的滤波效果。

It is difficult to identify the ideal signals in the self-adapting digital filter.In order to solve this problem,taking account of the mean squared error and the characters of high-frequency signal,this paper puts forward a new self-adapting digital filter.252 real data are used to test the effects of the self-adapting filter.In order to evaluate the filter effects,Back-Propagation（BP）neural network and Support Vector Machine（SVM）are respectively employed to classify the results of the data sets.The experimental results show that this method has the best performance among all filtering methods.