Title :
On-line spectral estimation of nonstationary time series based on AR model parameter estimation and order selection with a forgetting factor
Author :
Goto, Satoru ; Nakamura, Masatoshi ; Uosaki, Katsuji
Author_Institution :
Dept. of Electr. Eng., Saga Univ., Japan
fDate :
6/1/1995 12:00:00 AM
Abstract :
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)
Keywords :
autoregressive processes; electroencephalography; information theory; least squares approximations; medical signal processing; online operation; parameter estimation; recursive estimation; spectral analysis; time series; AIC; AR model parameter estimation; EEG; computer simulation; electroencephalogram; forgetting factor; model construction; nonstationary time series; on-line order determination; on-line parameter estimation; on-line spectral estimation; order selection; recursive least squares ladder estimation algorithm; Brain modeling; Computer simulation; Electroencephalography; Knowledge engineering; Least squares approximation; Least squares methods; Parameter estimation; Recursive estimation; Signal processing algorithms; Stochastic systems;
Journal_Title :
Signal Processing, IEEE Transactions on
