摘要
尝试将基于小波变换的数据压缩应用于窗口因子分析，在很大程度上克服了窗口因子分析直接处理原始信号时人工寻找最佳窗口的困难．该方法的数据分析结果表明，在压缩比高达８∶１的情况下，原始信号中的有用信息几乎没有丢失，窗口因子分析的解析时间则大为缩短，获得了有意义的解析结果．同时，小波变换具有的滤除高频噪音的优良性质使压缩信号的信噪比亦得到了改善，这对于分析结果的准确度是有帮助的．
Wavelet transformation(WT) is being widely applied in many fields. Data compression based on this method is employed to pretreat signals for Window Factor Analysis(WFA). Though a powerful tool for an evolving procedure, WFA cause a lot of trouble for determining the best window is tedious because of much human interference. In this paper, WT is used to perform data compression, then the compressed signal is treated by WFA. Results show that even with a compression ratio of 8∶1, most information contained in the original signal can be retained after treatment by WT, and the time comsumed by WFA is found to be greatly reduced, which can offset the flaw of WFA to a great extent. On the other hand, noise involved in the original signal can also be removed for its higher frequency, which contributes to the accuracy of WFA results.
