滑动平均

非同分布NA列滑动平均过程的完全收敛性

Complete Convergence of Moving Average Process for Non-identically NA Sequences

基于Kalman滤波的自回归滑动平均信号信息融合Wiener滤波器

Kalman filtering-based information fusion Wiener filter of autoregressive moving average signals

SAR图像分割的多尺度自回归滑动平均模型方法

A New Method for Segmentation of SAR Imagery Based on MARMA ( Multiscale Autoregressive Moving Average ) Model

给出了混合自回归滑动平均模型参数估计的EM算法和定阶准则。

The EM algorithm for estimation of this model is given and shown to work well .

基于改进的滑动平均滤波器的DDoS攻击检测

A DDoS intrusion detection method based improved slip average filter

同时还提出了辨识滑动平均（MA）模型参数的一种新的自适应Kalman滤波算法。

A new adaptive Kalman filtering algorithm is also given for identifying the parameters of moving average ( MA ) model .

将一种基于小波分析的自回归滑动平均求和（ARIMA）模型用于月径流的预测。

A wavelet analysis-based ARIMA model is proposed to forecast monthly runoff .

基于自回归滑动平均模型（ARMA）的运动目标检测。

Moving target detection basd on the auto-regressive and moving average model ( ARMA ) .

基于RLS的自回归滑动平均模型的两阶段辨识方法

Two-stage Identification Methods for ARMA Models Using RLS

本文分析了自回归滑动平均（ARMA）模型的频域特性；

This paper focusses on analysing properties of Autoregressive Moving Average ( ARMA ) model in frequency domain .

运用随机分析的方法建立了一个关于RED（randomearlydetection）队列长度及其指数加权滑动平均值（exponentiallyweightedmovingaverage，EWMA）的随机模型。

A stochastic model of the random early detection ( RED ) queue length and its exponentially weighted moving average ( EWMA ) value is developed based on stochastic analysis .

本文采用自回归滑动平均模型（ARMA）对电力负荷进行了预测。

In this paper , autoregressive moving average model ( ARMA ) is used to forecast the power load .

应用自回归滑动平均（ARMA）模型对大跨度薄膜结构随机风场进行了数值仿真；

Auto-regressive moving average ( ARMA ) model is presented for synthesizing the stochastic wind field on membrane structures .

在算法库中，除了部分的常规预测算法，如滑动平均、指数平滑、线性回归等，还加入了BP神经网络算法进行预测。

In the arithmetic base , besides some general predict algorithm as glide average , exponential smoothness , linearity regress , etc , it adds BP neural network algorithm for forecast .

提出了一种基于自回归滑动平均（ARMA）谱估计的医用多幅红外热图动态分析的方法。

A dynamic analysis method based on ARMA ( auto - regressive-moving-average ) models is proposed for medical infrared thermal images .

本文在已知VonKarman功率谱密度函数的情况下，选择利用自回归滑动平均（ARMA）模型来仿真风速。

This paper uses Auto-regressive moving-average ( ARMA ) model to simulate the wind records based on Von Karman spectral .

首先导出了二阶称重系统的自回归滑动平均模型（ARMA）；

The Auto - Regressive - Moving - Average ( ARMA ) model for the second order weighing system is firstly derived .

提出了将ARMA（自回归滑动平均模型）数学模型预测法与基于径向基函数的神经网络相结合的混合预测方法。

The hybrid forecast approach of combining the ARMA mathematical model forecast approach and Radial Basis Function neural network approach is proposed .

本文还着重介绍了VaR预测基于参数方法的指数加权滑动平均（EWMA）模型及其最新的发展。

We focus mainly on a promising approach of forecasting VaR , namely exponentially weighted moving average ( EWMA ) model and its latest new developments .

数值模拟结果和实际地震数据处理结果表明：自回归滑动平均（ARMA）模型比滑动平均（MA）模型具有参数节省、模型更为高效的特点；

The results of numeric simulation and real seismic data processing showed that the ARMA model was characterized by parameter-economic and high efficiency in comparison with MA model ;

另一方面，作为一种时域线性回归方法，自回归滑动平均模型（ARMA模型）也可被用于识别的结构参数识别。

On the other hand , the Au-to-regressive and moving average ( ARMA ) model , as a time-domain method , has been widely employed to identify structures .

用墨西哥帽小波和哈尔小波函数分析了我国气温变化的突变点位置，并用气温序列的5a滑动平均序列计算了信噪比（S/N），进一步验证了突变点的位置。

By using Mexican-hat wavelet and Haar wavelet transform , the abrupt change points of Chinese temperature in the last 120 years are discussed .

为消除稳态误差及改善零偏稳定性，数字控制器中加入积分环节和滑动平均滤波器，并引入PID控制算法改善系统动态特性。

In order to eliminate stably state error and improve zero bias stability , integral and moving average algorithm can be applied to the digital controller , and PID control algorithm is also introduced for improving dynamic performance of the system .

该文针对风速随机变化的特性，在风速统计特性研究的基础上，用自回归滑动平均（ARMA）方法建立了具有一定功率谱密度特性的风速模型。

This paper deals with stochastic characteristic of the wind speed , and gives an auto-regressive moving-average ( ARMA ) model for wind speed subjected to particular power spectral density .

根据带控制变量的非线性自回归滑动平均（NARMAX）模型理论，建立了锚泊线的系统模型。

A system model of a mooring line was constructed according to the NARMAX model theory .

本文采用矩阵的Kronecker积及拉直运算，获得了系数为滑动平均时，GAR（p）模型的一般平稳性条件，所用的方法具有普遍性。

This paper presents a stationary condition of GAR ( P ) with Kronecker products and straightening operation . This method can be generalized to normal GAR ( P ) models .

本文利用时间序列谱分析和卡尔曼滤波的方法讨论了两个随机过程，主要是自回归滑动平均（ARMA）过程，的叠加问题。

Using the methods of time series spectral analysis and Kalman filter , this article discussed the additive problems of two stochastic processes , mainly Auto Regression Moving Average ( ARMA ) processes .

本文基于噪声序列具有重尾分布的因果、平稳自回归滑动平均[ARMA（p，q）]过程，给出了其逆自相关函数的定义，并且给出了逆自相关函数的G-谱估计。

We consider a causal , stationary , autoregressive , moving average [ ARMA ( p , q ) ] process with heavy tailed noise variables . We develop the definition of the inverse autocorrelation function , and obtain the G-Spectral estimator of the inverse autocorrelation function .

针对基于非平稳时序的产品需求量预测方法存在的问题，研究了人工神经网络（ANN）与自回归滑动平均（ARMA）模型的集成建模与预测方法。

A new model of integrating artificial neural network ( ANN ) with auto regressive moving average ( ARMA ) is studied to handle existing problems of forecasting methods of product consumption based on non-stationary time series .

发现了Kalman滤波器和Wiener滤波器之间的变换关系，Wiener状态估值器可由Kalman估值器通过自回归滑动平均（ARMA）新息模型得到。

The transformation relationship between the Kalman filters and Wiener filters is discovered , the Wiener state estimators can be obtained from the Kalman estimators by means of the autoregressive moving average ( ARMA ) innovation model .