河川径流是一种复杂的非线性时间序列。
Stream flows are sorts of complicated nonlinear time series.
引入了非线性时间序列的局部投影消噪算法。
A local projective noise reduction for nonlinear time series is here introduced.
RBF网络对非线性时间序列具有很高的建模精度；
RBF network can model nonlinear time series with high precision;
提出了一种非线性时间序列混沌特征的自动提取方法。
A new method is put forward, which can implement auto-extracting of chaos features of nonlinear time series.
门限自回归模型是一种新近创立的非线性时间序列摸型。
The threshold autoregressive model is a kind of non-linear time series model recently established.
本文将混沌方法引入具有非线性时间序列的降雨量分析。
In this paper, the chaos theory is introduced to analyze nonlinear time series of rainfall.
识别混沌是对非线性时间序列进行分析、预测、控制的基础。
How to identify chaos is the foundation of analysis, prediction and control of nonlinear time series.
提出了一种基于相重构和主流形识别的非线性时间序列降噪方法。
A noise reduction method in nonlinear time series based on phase reconstruction and manifold learning was proposed.
门限自回归模型（TAR）是一种分段线性的非线性时间序列模型。
Threshold autoregressive model (TAR) is a nonlinear sequential model which is segmentedly linear.
针对神经网络的特点，探讨了神经网络对非线性时间序列预测的应用。
Based on specific features of the neural network, this paper is concerned with its application to prediction of nonlinear time sequence.
提出了一类新的用于非线性时间序列建模的混合自回归滑动平均模型。
We obtain some results as follows:In chapter 2, a new mixture autoregressive moving average model is proposed for modeling nonlinear time series.
试想，要真实地反映出这些非线性时间序列的本质，就必须使用非线性工具。
It must need nonlinear method to reflect essence of the time series veritably.
时间序列的非线性检测对于非线性时间序列分析、混沌特性研究有着重要意义。
Test of nonlinearity of time series is very important for nonlinear time series analysis and study of chaotic dynamics.
提出了一类用于非线性时间序列建模的混合自回归滑动平均模型(MARMA)。
A mixed autoregressive moving average (MARMA) model is proposed for modeling nonlinear time series.
利用非线性时间序列分析方法，以汉语语言认知为例，探讨语言认知系统的动力学特性。
By using the method of nonlinear time series analysis and taking the Chinese language cognition as an example, the dynamic characteristics of language cognition system are discussed.
与现有的非线性时间序列消噪算法不同，基于主流形的消噪算法更强调时间序列的整体结构。
Different from the existent noise reduction methods in nonlinear time series, the method based on principal manifold learning emphasized more on the global structure of time series.
本课程是博士生计量经济学系列课程的高级内容，介绍非线性时间序列的理论和方法的前沿研究。
The course is the advanced part in a PhD econometrics sequence. It provides developments in theory and methods of nonlinear time series econometrics.
依靠非线性时间序列分析方法提取重构动力系统的非线性或混沌特征参数，可以达到识别的目的。
The targets recognition can be reached by extracting the features of the reconstructed dynamics using nonlinear methods.
由于这些变量具有非线性时间序列数据，用人工神经网络(ANN)将使用反向传播算法作为学习算法。
Since these variables are characterized as nonlinearities time series data, Artificial Neural networks (ANN) will be employed using back propagation algorithm as learning algorithm.
本文提出了基于小波网络的非线性时间序列预报模型，探讨了非线性时间序列预报在故障预报中的应用。
Wavelet network based nonlinear time series prediction model is submitted, and nonlinear time series prediction and its application in fault prediction are discussed in this paper.
本文通过非线性时间序列分析的方法来分析心音时间序列，获得有关冠状动脉阻塞的血液动力学特征信息。
Nonlinear time series analysis is applied in analyzing heart sounds for acquiring hemodynamic character of partly or completely occluded coronary artery.
设计了模型结构和参数分别进化，共同识别方案，实现对非线性时间序列分析模型结构和参数进行全局最优搜索。
A new stepped evolutionary scheme is designed to search the global optimal structure and parameters of the nonlinear time series model.
相关维数是定量描述非线性时间序列的一个重要参数，在脑电、心电等生物医学信号的特征描述方面得到了广泛地应用。
Correlation dimension is an important parameter to measure a nonlinear time sequence quantitatively, and it is widely used to analyze biomedical signal, such as EEG and ECG.
从信息论角度出发，利用神经网络非线性时间序列预测模型，构造了油田产油量、产水量的多维时间序列神经网络预测器。
In this paper, using neuron network models of nonlinear multidimensional time series prediction, neuron network predictors for the oil production and water production of oil fields were constructed.
计算结果表明，对于岩土体工程中的一维监测数据，通过非线性时间序列分析方法可以对其进行预测分析，该方法具有较高的实用价值。
The result shows that, based on the one-dimensional monitoring data, the displacement can be predicted by the method of nonlinear time series, and the method has practical value.
由于现实世界中时间序列多数是非线性的，而现有的时间序列聚类问题大多是基于线性时间序列模型进行聚类的，提出了可以用于非线性时间序列的聚类方法。
Most of the popular clustering methods are designed for the linear time series, assuming that the stationary time series can be fitted by linear model. In fact, the true word is nonlinear.
建立了一个时间序列的门限自回归的预测模型，为股票市场的非线性研究这一前沿领域作了一点新的尝试。
Set up one time door limit prediction model of autoregression of array, study for nonlinearity of stock market this front field make new try a bit.
其次，对网络时延(RTT)特性进行了分析，利用线性和非线性方法对从互联网上采集的RTT时间序列进行统计分析。
Next, the thesis analysis the characterization of Roundtrip time delay (RTT). The RTT time series collected from the Internet are studied statistically by using both linear and nonlinear methods.
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.
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.
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