AR model is wide used time series model.
时间序列模型主要是自回归模型。
Research of ar model spectrum estimation theory.
AR模型谱估计理论研究。
AR model is the common method in sequence modeling.
AR模型是时序建模的常用方法。
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。
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。
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。
The Maximum Entropy method is a kind of parameter spectrum estimation method based on ar model.
最大熵谱估计法是以AR模型为基础的一种参数谱估计方法。
A method that ar model is applied to condition monitoring of deep hole processing is put forward.
提出一种用时间序列ar模型进行深孔加工状态监测的方法。
With the experiment the characteristic of the step factor and the order of ar model are researched.
以实验的方法研究了步长因子的特征及模型阶数的选取。
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。
With bispectrum analysis, an ar model parametric bispectrum estimation is presented for radar target echoes.
本文利用双谱分析方法，提出用非高斯ar模型对雷达目标回波信号进行参数化双谱估计。
AR Model method is of definitive concept and less interference factors, thus its correction result is satisfactory.
AR模型方法概念清楚，受干扰因素少，效果很好。
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。
Second, a three-layer BP neural network was designed to classify the muscle movement of forearm with AR model coefficient.
其次，设计了一个三层的BP神经网络，利用AR系数对手臂的各种肢体动作进行运动模式的分类。
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。
For the end effect in the process of empirical mode decomposition, the envelope extension algorithm by using AR model is proposed.
针对经验模态分解过程存在的边界效应问题，提出了利用AR模型进行包络延拓的边界处理算法。
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。
After difference disposal is applied to vibration signals, AR model is applied to signals collected in course of deep hole processing.
对所采集的深孔加工过程中的振动信号先进行差分处理，再进行AR建模。
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。
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。
It shows that an ar model is difficult to predict a sudden surge, because errors and delay are too large to be ignored in multi-step predication.
多步预测的误差和滞后现象显示AR模型难以预测突发性的喘振现象。
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。
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。
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。
A linear ar model is set up to be applied in real-time flood forecasting. Two criterion AIC and BIC are used to decide the exponent number of the linear ar model.
建立线性自回归模型，应用于洪水实时预报，并应用aic、BIC这两种准则以确定自回归模型的阶数。
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。
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。
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。
This article issues a new viewpoint and method in modeling for time series based on ar model. The method is able to give less calculating and to be programmed on computer.
提出了基于自回归(AR)模型对时间序列统一建模的新观点和方法，可大大减少计算量，并在微机上编程实现。
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