非平稳时间序列的状态空间建模技术被用于陀螺漂移分析。
A state space approach for the modeling of nonstationary time series is presented.
将非平稳时间序列的状态空间建模方法用于陀螺过渡过程的分析。
Stationary time series state space modeling method for the analysis of the transition process gyro.
经济过程中的结构突变，对非平稳时间序列的分析具有非常重要的影响。
The structure mutation during the economic process has very important influence on the analysis of non-smoothed time series.
茧丝纤度曲线的预测研究茧丝纤度曲线可视为是长度有限且随机变动的非平稳时间序列。
Size curves of cocoon filaments can be regarded as non-stationary time series with finite length varying at random.
先将非平稳时间序列进行经验模式分解，再对各个分量分别建模，最后将各分量预测结果进行组合。
Empirical mode decomposition is used for pre-processing. Decompose time series, then make models separately and combine all the values.
将小波分析理论、灰色预测理论和时间序列预测法组合进行需水量的预测，为原始非平稳时间序列的预测应用拓展了空间。
The space of prediction and application of non-stationary time series were expanded through the combined model of wavelet analysis, gray and time series prediction methods.
在高斯假定下得到非平稳时间序列的协方差矩阵的转移形式。对一个实际的地震过程进行的数字研究结果证明本文方法是有效的。
The transition of the covariance matrix of the nonstationary time series is obtained with Gaussian assumptions. An actual earthquake is studied by the method proposed and satisfactory res…
本文用时间序列分析的方法，在机床连续切削和非连续平稳切削状态下识别机床的固有频率。
In this article, the natural frequencies of machine tools under continuous cutting and steady non-continuous cutting conditions are identified with time series method.
单位根检验是计量经济学中检验时间序列数据平稳性的最重要工具，而协整检验则是用来判断非平稳变量之间是否存在长期均衡关系的常用方法。
As an important tool of testing time series stationarity, unit root test is always used, and cointegration test is also often implied for judging long equilibrium between nonstationary variables.
数值实验表明，SVR方法对非平稳的金融时间序列具有良好的建模和泛化能力。
Numerical test results show that SVR has good ability of modeling nonstationary financial time series and good generalization under small data set available.
将现场测得的非平稳振动序列通过ARIMA模型和标准化处理，转化成标准正态平稳时间序列。
Through ARIMA model and standardization, the non stationary vibration series acquired in the field were transformed to stationary time series normally distributed.
由于股票预测是不确定、非线性、非平稳的时间序列问题，传统的方法往往难以取得满意的预测效果。
Because stock forecasting is a uncertain, nonlinear and nonstationary time series problem, it is difficult to achieve a satisfying prediction effect by traditional methods.
研究结果表明，小波变换是分析非平稳随机时间序列的有效工具，在水文水资源领域应用潜力很大。
The results indicate that the wavelet transform is an effective tool for nonstationary stochastic series analysis, which has great potential in hydrology and water resources research.
验证了时间序列分析方法在非平稳随机信号处理方面的可靠性；
The reliability of the time-series analysis method in processing unsteady random signals is verited.
由于实际信号常常具有非平稳特征，直接应用AR模型进行时间序列分析，得不到理想的效果。
The real signals have often non-stationary characteristic, so if we analyse these time series using AR model directly, we cant obtain design result.
方法用于对非平稳金融时间序列进行了符号化转换，实验结果表明该方法是有效的。
The proposed method is applied to unsteady financial time series symbolization. Experimental result shows that the method is effective.
然而石油期货价格具有时间序列数据的典型特点，即非线性和非平稳性，这给价格的预测带来了极大的困难。
However, the oil futures prices involve the typical characteristics of time series data, nonlinearity and nonstationarity, which brings insuperable difficulties in the price forecasts.
非线性，非平稳的时间序列经过经验模分解，可以得到一组内模函数和一个基本的趋势项。
Nonlinear and nonstationary time series are decomposed into a series of instrinsic mode functions and a residual trend item by the empirical mode decomposition (EMD).
针对故障率时间序列的非线性与非平稳特性，提出一种基于支持向量经验模态分解(SVEMD)的预测方法。
A prediction method based on support vector empirical mode decomposition (SVEMD) is proposed to deal with the non-linearity and non-stationarity of failure rate data.
针对故障率时间序列的非线性与非平稳特性，提出一种基于支持向量经验模态分解(SVEMD)的预测方法。
A prediction method based on support vector empirical mode decomposition (SVEMD) is proposed to deal with the non-linearity and non-stationarity of failure rate data.
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