1) Kalman filter/nonstationary time series
卡尔曼滤波/非平稳时间序列
2) Non stationary time series
非平稳时间序列
1.
Therefore a study on the predicting model with non stationary time series is made.
目的许多大型旋转机械运行工况恶劣 ,非平稳、非线性特征明显 ,以及各种突发性、偶然性因素的影响 ,给基于振动信号处理的状态预测和状态维护分析带来困难 ,为此研究了非平稳时间序列预测模型。
2.
By using the proposed segmental feature dependent non stationary time series model, the new model not only achieves the modeling of correlation between different scale features but also implicitly models the correlation among neighboring frames in frame scale via parametric mean trajectory function.
该模型采用描述谱参数轨迹的段特征 ,在段尺度上实现了对语音信号帧间相关性的显式建模 ;采用段特征依赖的非平稳时间序列产生模型 ,实现了不同尺度特征间的相关性建模 ,并在帧尺度上通过参数化的均值轨迹函数 ,实现了对语音信号帧间相关性的隐式建模 。
3.
This paper introduced a method of wavelet based analysis and forecasting for non stationary time series.
提出了基于小波变换的非平稳时间序列分析预测方法 。
3) non-stationary time series
非平稳时间序列
1.
Study on the methods for modeling and forecasting gyro s drift performance based on non-stationary time series;
基于非平稳时间序列的陀螺漂移性能建模与预测方法研究
2.
Non-stationary time series prediction based on wavelet analysis and AR-LSSVM;
基于小波变换和AR-LSSVM的非平稳时间序列预测
3.
To build an appropriate mathematic model of the random drift of flexible gyro,two methods are discussed,using non-stationary time series analysis and using stationary time series analysis based on wavelet discomposition.
以挠性陀螺的随机漂移为研究对象,采用非平稳时间序列分析法和基于小波分解的平稳时间序列分析法,建立相应的随机漂移模型。
4) nonstationary time series
非平稳时间序列
1.
The moving average model-based nonstationary time series method is used in the model distinction, parameter estimation, and new information prediction in this paper.
根据大坝裂缝开度实测资料的特点,将裂缝开度{xt}看成一系列时刻t1,t2,…,tn得到的时间序列,采用基于滑动平均模型MA(q)的非平稳时间序列法,对其进行模型识别、参数估计和新息预报。
2.
? A state space approach for the modeling of nonstationary time series is presented.
非平稳时间序列的状态空间建模技术被用于陀螺漂移分析。
3.
This method is used to build forecasting models on the ideal time series from 33-mode Lorenz system,and especially the prediction on nonstationary time series are tested and analyzed.
简要介绍了基于统计学习理论的支持向量机方法的基本思想和原理,利用该方法对33模Lorenz系统的理想混沌时间序列建立预测模型,并对在此基础上产生的非平稳时间序列进行预测试验研究。
5) robust Kalman filter
稳健卡尔曼滤波
6) sequential Kalman filter
序贯卡尔曼滤波
补充资料：卡尔曼滤波
见波形估计。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条