【摘要】 在地震、语音、心电等时间序列信号的识别问题中,常需对时间序列进行特征抽取。本文提出一种时间序列特征抽取的新方法,它将时间序列分解为两部分,分别抽取特征。具体实现是用 AR 系数与维纳滤波器系数结合起来形成特征向量。此法可用于地震信号的特征抽取,识别沉积序列,帮助推断沉积相。计算机实验结果表明,方法是很有效的。更多还原

【Abstract】 In the recognition problem of time series signals such as seismic,acoustic,andEEG,ECG signal,it is necessary to extract features from time series.In this pa-per,a new method for feature extraction of time series is proposed,which decom-poses time series into two parts and extracts features respectively.Its implementation is by AR model and Wiener filter,AR coefficients and Wiener filter coefficientsare combined into feature vector.As an example of application,this method is usedto extract features from seismic signal,in order to recognize sedimentary sequenceand then help the inference of sedimentary faces.The computer experimental resultshave shown that the method is quite effective.更多还原