When a white noise interferes with the controller, a time series autoregressive (AR) model is built using the sampled experimental data.
当白噪声干扰方向控制器时，可以用采样数据建立时间序列的自回归模型。
It will set up ar model, analyze power spectrum, and calculate transfer function and delay time, thus several fundamental problems in the research of robot wrist sensor can be solved.
建立了AR模型，分析了功率谱，计算了传递函数和滞后时间，解决了机器人腕力传感器研究中的若干基础性问题。
Validated by the experiments, AR model spectrum estimation method is a good way to process flow signal and the results of it is more accuracy than the results that gain by count method.
通过实验验证，AR模型谱估计可以作为一种较好的方法，用来处理流量计的输出信号，并且此方法得出的结果比计数方法得出的结果精度高。
This paper USES several criteria to estimate the order of the AR model and the influence for the distance measurement outcomes.
主要探讨在这种方法中利用不同的定阶准则建立相应的AR模型及其对距离测度结果的影响。
Ar model based distance measurements with EEG signals are well reliable for the injury detection of the central nervous system.
基于AR模型的EEG信号距离测度方法可以较好地表征中枢神经系统损伤的情况。
Auto regressive (AR) modeling is widely used in signal processing. The coefficients of an AR model can be easily obtained with an LMS algorithm.
自适应(AR)模型是数字信号处理中广为应用的一种模型，它的系数可以通过LMS算法求解。
A fault diagnosis approach for rotor systems based on AR model and support vector machine is proposed.
提出了基于AR模型和支持向量机的转子系统故障诊断方法。
X spectrum processing method based on AR model was proposed.
提出采用AR模型处理X光谱的方法。
This paper proposes the prediction method of time series based on AR model and forecasts the development trend of weighted length of fiber for hydrocyclone by this method.
以时间序列为理论基础，利用时间序列分析方法对水力旋流器的筛分性能建立了AR模型，并依据该模型对纤维重均长度变化趋势进行了预测分析。
AR model is the common method in sequence modeling.
AR模型是时序建模的常用方法。
The rotor angle predicting method adopting the forgetting index of auto regression (AR) model arithmetic is presented.
提出了采用遗忘因子的自回归（AR）模型的功角预测方法。
We analyse statistics properties of ground clutters and study AR model of correlated clutters power spectral density.
分析了地杂波统计特性，研究了相关雷达杂波功率谱特性的AR模型及其模拟方法。
After the first water addition, we adopt AR model to predict the stable value of sand compactibility to shorten the time mixing the sand.
第一次加水后，对型砂紧实率稳定值采用AR模型进行预测，以缩短型砂混制时间。
The order of the AR model can be determined by Final Predictio nError (FPE) criterion.
而AR模型的阶次由最终预测误差（FPE）判据确定。
AR model is wide used time series model.
时间序列模型主要是自回归模型。
Secondly, the locally linear prediction and ar model is introduced for the chaos sequences have the character of local predictability.
其次，根据混沌特性中的短时可预测性介绍了局部线性拟合和AR模型预测算法。
On the basis of traditional time series analysis and modeling methods, the thesis puts forward a new complete and simply identification method by using ar model.
本文在传统时间序列分析建模方法的基础上，提出了用AR模型的新的完整而又简单的辨识方法。
By the statistical analysis of ship motion attitude and equivalent argument about ARMA model and ar model, ar model was identified to be the mathematic model for ship motion attitude prediction.
通过对舰船运动姿态统计分析，以及对ARMA模型和AR模型等价性论证，确定了AR模型作为船舶姿态运动预报的数学模型。
Count method and ar model spectrum estimation method are adopted respectively to experiment.
分别采用计数的方法和AR模型谱估计的方法进行实验。
After the mathematics principle which use simulating well and Guassian probability distribution are reviewed, the simulation method of correlation Gaussian clutter based on ar model is presented.
回顾了产生均匀分布、高斯分布随机序列的数学原理，提出了基于AR模型的相关高斯杂波仿真方法。
In this paper the description of the ship motion with ar model, the selection of the order of the ar model and the construction of the K steps advanced adaptive predictor are discussed.
本文讨论了船舶在不规则海浪中运动的AR模型描述方法和AR模型阶的选择，并用自适应预报的方法提出了超前k步的自适应预报器。
Research of ar model spectrum estimation theory.
AR模型谱估计理论研究。
For the features of disc proportioning system's lag and discharge rate's fluctuation, applying time series analysis, a disc discharge rate prediction model based on ar model was set up.
针对原料场圆盘配料系统下料量检测滞后和料量随堆料机进退变化较大的特点，应用时间序列分析方法建立了基于AR模型的圆盘下料量预测模型。
Experiments on the method show that AR model spectrum has the advantage of heving a continuous smooth curve, by which the damage factor can easily be obtained.
结果表明，AR模型谱具有连续光滑易于提取损伤因子等特点，应用于主动监测信号的定量表征是非常有效的。
According to the structure characteristics of a time varying time series model, a new recursive parameter estimation algorithm of the time varying ar model is proposed.
根据对一类时变时间序列模型结构特点的研究，提出了一种时变ar模型的递推参数估计算法。
The ARMA model was used to describe the prior distribution of observed discharge and the ar model was adopted to simulate the likelihood function of forecasting error.
该模型采用ARMA模型描述实测流量的先验分布，采用AR模型模拟预报残差的似然函数，并假定先验分布和似然函数均服从正态分布。
The results showed that the change of time-varying parameters (coefficient) in dynamic AR model has a regularity. Its increments are piled up by some simple period functions.
结果表明，动态自回归模型时变参数（时变系数）的变化是有规律的，其增量大体上是一些简单周期函数的叠加。
The real signals have often non-stationary characteristic, so if we analyse these time series using AR model directly, we cant obtain design result.
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。
Based on measured data of micro silicon gyro and time-series theory, the AR model of gyro static drift is established, then the continuous-time differential equation is got.
利用微硅陀螺测量的数据，运用过程辨识理论和时间序列分析方法，建立了陀螺静态漂移的自回归（AR）模型，进而得到连续微分方程。
Based on measured data of micro silicon gyro and time-series theory, the AR model of gyro static drift is established, then the continuous-time differential equation is got.
利用微硅陀螺测量的数据，运用过程辨识理论和时间序列分析方法，建立了陀螺静态漂移的自回归（AR）模型，进而得到连续微分方程。
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