Title :
Identification of autoregressive signals in colored noise using damped sinusoidal model
Author :
Hasan, Md Kamrul ; Chowdhury, A. K M Z Rahim ; Khan, M. Rezwan
Author_Institution :
Dept. of Electr. & Electron. Eng., Bangladesh Univ. of Eng. & Technol., Dhaka, Bangladesh
fDate :
7/1/2003 12:00:00 AM
Abstract :
This work addresses a new method for autoregressive (AR) parameter estimation from colored noise-corrupted observations using a damped sinusoidal model for the autocorrelation function of the noise-free signal. The damped sinusoidal model parameters are first estimated using a least-squares based method from the given noisy observations. The AR parameters are then directly obtained from the damped sinusoidal model parameters. The performance of the proposed scheme is evaluated using numerical examples.
Keywords :
autoregressive processes; least squares approximations; noise; parameter estimation; AR parameter estimation; AR signal identification; autocorrelation function; autoregressive parameter estimation; colored noise-corrupted observations; damped sinusoidal model parameters; least-squares based method; Additive noise; Autocorrelation; Biomedical engineering; Colored noise; Econometrics; Gaussian noise; Parameter estimation; Signal processing; Signal to noise ratio; Stochastic resonance;
Journal_Title :
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
DOI :
10.1109/TCSI.2003.813954