提出了一种新的概率函数计算方法，用于研究金融时间序列在方差波动方面的多重分形特征。
A new probabilistic function for studying the multi-fractal features on the volatility of variance of financial time series is proposed.
第四部分是多重分形谱参数在预测高频股价时间序列在下一个交易周波动幅度方面的应用。
The theoretical anomalous characteristics of multifractal spectra on high-frequency stock-price time series are firstly deduced during prices fluctuate sharply.
采用新型多重分支时间延迟神经网络进行混沌时间序列预测研究。
A new multi-branch time delay neural network is adopted to conduct prediction research on chaotic time series.
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