查询词典 analysis of time series

The analysis of time series structure is an important premise for studying the original series.

时间序列的结构分析是深入研究原始序列的重要前提。

The analysis of time series is a primary method for extracting the anomaly information of earthquake activity.

地壳形变和地面温度异常是构造地震活动监测的两项重要指标，时间序列分析是提取地震活动异常信息的主要方法。

This section simply introduces the basic principles of the conventional analysis of time series (mean, variance, standard deviation; covariance and correlation coefficient; autocovariance and autocorrelation coefficient), frequency spectrum analysis and wavelet analysis.

本文简单地介绍了传统时序分析（包括平均值、方差和标准差；协方差和相关因子；自协方差和自相关因子）、频谱分析和小波分析的基本原理。

On the basis of the data obtained from the field observations and wind-tunnel modelling, the calculations and comparisons on probability distribution and density, linear correlation analysis of time series, conditional probability density and so on of wind speeds and directions between various sites are made with the aid of statistical analysis of time series, and changes of these variables with height and representativeness of observation period of meteorological data are also discussed.

本文以现场气象观测和风洞模拟实验数据为基础，通过对时间序列进行的统计分析，计算和比较了各个厂址风速、风向的概率分布、概率密度、时间序列线性相关分析、条件概率密度等，还对它们随高度的变化情况、观测时段代表性等问题进行了讨论。

The basical ideas, arithmatic methods and applied conditions of reduction of partial least squares and discrete wavelet transformation, logitboost, random forests and fuzzy kendal discriminate analysis of microarray gene expression data, ordinal discriminate analysis of time series multivariate data and varied-coefficient-logistic-regression-model discriminate analysis of the data with varied regular pattern in itself.

本文对医学领域中判别分析方法的新进展做一综述，介绍了微阵列基因表达数据判别分析中偏最小二乘法降维、离散小波变换法降维、logitboost算法、随机森林、模糊核判别分析以及时间序列多元数据有序判别分析法、自身有变化规律数据的变系数logistic回归模型判别分析法的基本思想、算法和适用条件。

Dissertation introduced a brief analysis of time series, simple overview of the data compression technology in several common algorithms, wavelet algorithm and to focus on the wavelet analysis of the nature and characteristics of algorithm, introduced by wavelet data compression algorithm method.

论文主要介绍了关于时间序列的简要分析，简单概述了数据压缩技术的中的几种常用算法，并以小波算法为重点分析了小波算法的性质和特点，介绍了用小波算法进行数据压缩的方法。

For the singular spectrum analysis of time series, a method of constructing covariance matrix by using forth order cumulant is proposed. The method could restrain the Gaossian noise and symmetrical distributed noise mixed with chaotic signals.

对于时间序列的高阶奇异谱分析，提出了一种利用四阶累积量函数构造协方差矩阵的方法，该方法从理论上能有效地抑制叠加在混沌信号中的高斯噪声和对称分布噪声对重构结果的影响。

Under this background a new theory that combined with techniques derived from chaos theory, Shannon information theory, complexity analysis of time series, is presented, that is multi-order information theory of brain cortex. Then, its application to EEG analysis in different physiological states is investigated in this paper.

在对非线性动力学数值统计量方法用于不同生理状态下的脑电分析进行研究后，本文在前人工作的基础上，提出了建立在非线性理论基础上的大脑多阶信息理论，并利用该理论对不同生理条件下脑电地多阶信息量特征进行分析，并结合人工神经网络理论，研究了该方法在解决医学临床几个重要问题中的应用，初步得到了有意义的结论。

An application of dynamic econometric analysis of time-series model to performance of investment on science and technology in China.

时间序列模型的动态计量分析方法在科研投入效果评价中的应用。

Resealed range analysis method is one of the good tools for studying fractal Brownian motion of time-series data and natural phenomena self-affine fractal, being applied widely for all time-series. In this paper, this method is used to analyze absolute geomagnetic Z component observations at Tianshui Observatory.

重标极差分析法(R/S， rescaled range analysis method)，是研究分数布朗运动及自然现象的自仿射分形的有力工具之一，对于所有时间序列分析都有着广泛的用途。

But in the course of internationalization, they meet with misunderstanding and puzzlement.

许多企业已经意识到了这一点，但在国际化的进程中，仍存在一些误区与困惑。

Inorder toaccomplish this goal as quickly as possible, we'll beteamingup with anexperienced group of modelers, skinners, and animatorswhosenames willbe announced in the coming weeks.

为了尽快实现这个目标，我们在未来数周内将公布与一些有经验的模型、皮肤、动画制作小组合作。