提出一种基于非线性自回归时间序列模型(gereral expression for linear and nonlinear auto-regressive mod-el,简称GNAR模型)的机械系统状态识别与故障诊断方法。利用采集系统工作过程中的特征信号建立GNAR模型;用主成分分析策略生成...提出一种基于非线性自回归时间序列模型(gereral expression for linear and nonlinear auto-regressive mod-el,简称GNAR模型)的机械系统状态识别与故障诊断方法。利用采集系统工作过程中的特征信号建立GNAR模型;用主成分分析策略生成模型特征量,对训练样本的特征量进行识别和分类,得到各种参考模式;将几何距离判别函数作为状态分类的原则,根据待判系统特征量与各类参考模式的Euclide距离进行状态识别和故障判别。对车床颤振试验数据及高速离心空气压缩机故障数据的分析表明,该方法快捷、高效,诊断成功率较好,具有良好的工程应用前景。展开更多
It is proved that a linearly recursive sequence of n indices over field F (n≥1) is automatically a product of n linearly recursive sequences of 1-index over F by the theory of Hopf algebras.By the way, the correspond...It is proved that a linearly recursive sequence of n indices over field F (n≥1) is automatically a product of n linearly recursive sequences of 1-index over F by the theory of Hopf algebras.By the way, the correspondence between the set of linearly recursive sequences of 1-index and F[X]° is generalized to the case of n-index.展开更多
A nonparametric test for normality of linear autoregressive time series is proposed in this paper.The test is based on the best one-step forecast in mean square with time reverse.Some asymptotic theory is developed fo...A nonparametric test for normality of linear autoregressive time series is proposed in this paper.The test is based on the best one-step forecast in mean square with time reverse.Some asymptotic theory is developed for the test,and it is shown that the test is easy to use and has good powers.The empirical percentage points to conduct the test in practice are provided and three examples using real data are included.展开更多
In this paper, the authors consider an adaptive recursive algorithm by selecting an adaptive sequence for computing M-estimators in multivariate linear regression models. Its asymptotic property is investigated. The r...In this paper, the authors consider an adaptive recursive algorithm by selecting an adaptive sequence for computing M-estimators in multivariate linear regression models. Its asymptotic property is investigated. The recursive algorithm given by Miao and Wu （1996） is modified accordingly. Simu- lation studies of the Mgorithm is also provided. In addition, the Newton-Raphson iterative algorithm is considered for the purpose of comparison.展开更多
In this paper, the relative dependence of a linear regression model is studied. In particular, the dependence of autoregressive models in time series are investigated. It is shown that for the first-order non-stationa...In this paper, the relative dependence of a linear regression model is studied. In particular, the dependence of autoregressive models in time series are investigated. It is shown that for the first-order non-stationary autoregressive model and the random walk with trend and drift model, the dependence between two states decreases with lag. Some numerical examples are presented as well.展开更多
文摘提出一种基于非线性自回归时间序列模型(gereral expression for linear and nonlinear auto-regressive mod-el,简称GNAR模型)的机械系统状态识别与故障诊断方法。利用采集系统工作过程中的特征信号建立GNAR模型;用主成分分析策略生成模型特征量,对训练样本的特征量进行识别和分类,得到各种参考模式;将几何距离判别函数作为状态分类的原则,根据待判系统特征量与各类参考模式的Euclide距离进行状态识别和故障判别。对车床颤振试验数据及高速离心空气压缩机故障数据的分析表明,该方法快捷、高效,诊断成功率较好,具有良好的工程应用前景。
文摘It is proved that a linearly recursive sequence of n indices over field F (n≥1) is automatically a product of n linearly recursive sequences of 1-index over F by the theory of Hopf algebras.By the way, the correspondence between the set of linearly recursive sequences of 1-index and F[X]° is generalized to the case of n-index.
基金This research is supported by the National Natural Science Foundation of China(No.19971093) the Knowledge Innovation Program of the Chinese Academy of Sciences (No. KZCX2-SW-118).
文摘A nonparametric test for normality of linear autoregressive time series is proposed in this paper.The test is based on the best one-step forecast in mean square with time reverse.Some asymptotic theory is developed for the test,and it is shown that the test is easy to use and has good powers.The empirical percentage points to conduct the test in practice are provided and three examples using real data are included.
基金supported by the National Natural Science Foundation for Young Scientists of China under Grant No.11101397the Natural Sciences and Engineering Research Council of Canada
文摘In this paper, the authors consider an adaptive recursive algorithm by selecting an adaptive sequence for computing M-estimators in multivariate linear regression models. Its asymptotic property is investigated. The recursive algorithm given by Miao and Wu （1996） is modified accordingly. Simu- lation studies of the Mgorithm is also provided. In addition, the Newton-Raphson iterative algorithm is considered for the purpose of comparison.
基金supported by the National Science Foundation of China under Grant No.71171193the Fundamental Research Funds for the Central Universitiesthe Research Funds of Renmin University of China under Grant No.10XNI001
文摘In this paper, the relative dependence of a linear regression model is studied. In particular, the dependence of autoregressive models in time series are investigated. It is shown that for the first-order non-stationary autoregressive model and the random walk with trend and drift model, the dependence between two states decreases with lag. Some numerical examples are presented as well.
