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Estimation of time series noise covariance using correlation technology
Authors:Tao MA  Jie CHEN  Wenjie CHEN  Zhihong PENG
Affiliation:School of Automation, Beijing Institute of Technology, Beijing 100081, China;Key Laboratory of Complex System Intelligent Control and DecisionMinistry of Education, Beijing Institute of Technology, Beijing 100081, China
Abstract:Covariance of clean signal and observed noise is necessary for extracting clean signal from a time series.This is transferred to calculate the covariance of observed noise and clean signal's MA process,when the clean signal is described by an autoregressive moving average (ARMA) model.Using the correlations of the innovations data from observed time series to form a least-squares problem,a concisely autocovariance least-square (CALS) method has been proposed to estimate the covariance.We also extended our w...
Keywords:Time series   Correlation technology   Covariance estimation   Least-square method
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