运用数字滤波、傅立叶变换，以及幅值分析和基于神经网络的专家系统等方法对信号进行监测和诊断。
In the structured system, signals are proceeded by low-pass filter, Fourier Trans form, range analyzing and expert system based on Neural Network.
提出了用小波神经网络（WNN）来定量研究高频金融时间序列“日历效应”，通过比较发现WNN 是比弹性傅立叶形式（FFF）回归技术更具优势的方法。
The paper proposes application of Wavelet Neural Network in high-frequency time series calendar effects' study. At last, the paper proves that WNN is better than classical FFF regression.
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