1) sequence matching based algorithm
时序分析方法
1.
After that, we use sequence matching based algorithm to analysis the capital flows in order to find a more precise method to identity suspicious transactions.
其次,本文采用了时序分析方法定量分析了商业银行资金流动数据,为识别可疑交易提供了更为精确的算法支持。
2) modern time-series analysis method
现代时间序列分析方法
1.
Using modern time-series analysis method,based on the autoregressive moving average(ARMA)innovation model and white noise estimators,a new two-stage decoupled Wiener filters are presented for descriptor systems with stochastic bias.
应用现代时间序列分析方法 ,基于ARMA新息模型和白噪声估值器 ,提出了一种分离随机偏差两段解耦Wiener滤波新方法 ,同两段解耦Kalman滤波理论相比 ,避免了解Riccati方程 ,实现了完全解耦。
2.
To discrete-linear systems with stained observe noises,based on the ARMA innovation model,using modern time-series analysis method,a new decouple Wiener trace filter method are presented.
对带有色观测噪声的离散线性系统 ,应用现代时间序列分析方法 ,基于ARMA新息模型 ,提出了一种解耦Wiener滤波新方法 ,仿真例子说明了本方法的有效
3.
Using modern time-series analysis method,based on the autoregressive moving av-erage(ARMA)innovation model and white noise estimators,state-input estimation two stage decoupled Wiener filters are presented for stochastic system s with non-determinate control input.
运用现代时间序列分析方法,基于ARMA模型和白噪声估值器,对一类控制输入存在不确知性的随机系统,提出了状态输入估计两段解耦Wiener滤波新算法,仿真例子说明了其有效性。
3) modern time series analysis method
现代时间序列分析方法
1.
By the modern time series analysis method, based on the autoregressive moving average(ARMA) innovation model, the multisensor single channel optimal information fusion Wiener filter is presented under the linear minimum variance fusion criterion for single channel ARMA signals with white observation noise.
应用现代时间序列分析方法,对于带白色观测噪声的单通道ARMA信号,基于ARMA新息模型,提出了多传感器线性最小方差最优信息融合Wiener滤波器,可统一处理滤波、平滑和预报问题。
2.
Using the modern time series analysis method,based on the autoregressive moving average (ARMA)innovation model and white noise estimators,this paper presents two new fixed point Kalman smoothers and two new forward fixed interval Kalman smoothers for linear discrete time invariant stochastic systems.
应用现代时间序列分析方法，基于ＡＲＭＡ新息模型和白噪声估值器，对线性定常离散随机系统提出了两种新的固定点Ｋａｌｍａｎ平滑器和两种新的正向固定区间Ｋａｌｍａｎ平滑器。
3.
By the modern time series analysis method, based on the autoregressive moving average(ARMA)innovation model,and white noise estimation theory,a distributed steady-state Kalman fuser with a three-layer fusion structure is presented,which consists of two weighted fusers and two composite fusers.
对带多传感器的线性离散随机广义系统,用奇异值分解将其化为两个降阶耦合子系统,应用现代时间序列分析方法,基于自回归滑动平均(Autoregressive moving average,ARMA)新息模型和白噪声估计理论,提出了带三层融合结构的分布式稳态Kalman融合器,它由两个加权融合器和两个复合融合器组成。
4) time series analysis method
时间序列分析法
1.
Application of time series analysis method in groundwater level dynamic forecast of Shenyang City;
时间序列分析法在沈阳市地下水位动态预报中的应用
2.
By means of time series analysis method,random drift signal output by oriention gyro in navigation system is analyzed under normal and fault conditions so as to obtain a fault identification method of gyro performance.
运用时间序列分析法对正常和故障情况下导航系统中方位保持部件陀螺仪输出随机漂移信号进行分析,得到一种判断陀螺仪性能故障的方法。
5) time series analysis
时间序列分析法
1.
Applying the method of time series analysis to forecasting the paddy water requirement;
时间序列分析法在水稻需水量预测中的应用
2.
This paper employs the neural network method, time series analysis method and recursive neural networks technology based on data mining and knowledge discovery to predict the iron and steel output.
文章使用基于数据挖掘和知识发现的人工神经网络法、时间序列分析法、递归神经网络技术来预测钢铁产量的方法,并将递归神经网络方法预测的结果与前面的两种方法的预测结果进行比较,比较的结果说明该方法是可行的。
6) 16S rRNA serial analysis method
16SrRNA序列分析方法
补充资料：时序
1.时间的先后;季节的次序。 2.节候;时节。 3.时间;光阴。 4.犹时世。 5.犹承序，承顺。言有条理。
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