Anomaly Processing Based on Wavelet Analysis

It is difficult to detect the anomalies of which the relationship among its attributes is very different from one another in a data set.Aiming at this problem,an approach based on wavelet analysis to detect and amend the anomalous samples is proposed in this paper.Taking full advantage of wavelet analysis characteristics of multiple scale and local analysis,this approach is able to detect and amend anomalous samples accurately.To realize the rapid numerical computation of wavelet translation for a discrete sequence,a modified algorithm based on Newton-Cores formula is also proposed.The test results show that the approach is feasible,with good effect and practicality.