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On-line spectral estimation of nonstationary time series based on AR model parameter estimation and order selection with a forgetting factor

机译:基于AR模型参数估计和遗忘因子阶次选择的非平稳时间序列在线谱估计

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摘要

A new method for on-line spectral estimation of nonstationary time series via autoregressive (AR) model construction is proposed. The method consists of on-line parameter estimation based on the recursive least squares ladder estimation algorithm with a forgetting factor and on-line order determination based on AIC with some modifications. The effectiveness of the proposed method is demonstrated by computer simulation study and applying to the actual data of electroencephalogram (EEG).
机译:提出了一种通过自回归(AR)模型构建非平稳时间序列在线频谱估计的新方法。该方法包括基于具有遗忘因子的递归最小二乘梯形估计算法的在线参数估计和基于AIC的在线顺序确定(进行一些修改)。通过计算机仿真研究证明了该方法的有效性,并将其应用于脑电图(EEG)的实际数据。

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