采用延迟坐标状态空间这种相空间重构方法，对非线性系统中的单一时间序列进行分析，从中恢复出系统内部存在的非线性动力学特性。
The delay-coordinate method is adopted to reconstructed the space phase, and to analyze the single time series in the non-linear systems and resume the nonlinear kinetics characteristics.
基于混沌动力系统相空间的延迟坐标重构和双线性表达式，设计了预测混沌时间序列的双线性自适应预测滤波器。
Based on the delay-coordinate reconstruction and bilinear expressions in the phase space of a chaotic system, a bilinear adaptive filter was designed to predict low-dimensional chaotic time series.
结果表明，GPS站坐标时间序列中白噪声甚至不是噪声的主要成分。
The result shows that the white noise in the time series of GPS site coordinates does not constitute the main part of noise.
采用线性插值及双线性插值得到预测点位置上的本征模态值。 结构由原风压场协方差分析得到的主坐标和上述新本征模态值获得未布置测压点位置的风压时间序列。
The linear interpolation and bilinear interpolation were employed to obtain the values of the proper modes on locations where the wind pressure time series are to be predicted.
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。
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。
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.
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