基本上{Xt}以三种现象显示: 平稳型时间数列(Deterministic time series ); 随机型时间数列(Stochastic time series); 混沌性时间数列(Chaotic time series).
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In order to study further this type of time series, it is necessary to extract deterministic and stochastic components.
为了进一步研究这种类型的时间系列，有必要提取确定性和随机成分。
Based on the deterministic and nonlinear characterization of the chaotic signals, a new reduced parameter nonlinear adaptive filter is proposed to make adaptive predictions of chaotic time series.
基于混沌动力系统的相空间延迟坐标重构，利用混沌序列固有的确定性和非线性，提出了用于混沌时间序列预测的一种少参数非线性自适应滤波预测模型。
A short-term prediction method developed on the basis of the deterministic chaos theory is used to predict the time series of pressure fluctuations in a gas-liquid bubble column with a single orifice.
应用混沌预测方法，对气液两相单孔鼓泡系统的压力波动时间序列进行了短期预测。
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