Title :
Adaptive AR modeling in Gaussian noise
Author :
Wu, Wen-Rong ; Chen, Po-Cheng
Author_Institution :
Dept. of Commun. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
Abstract :
The AR modeling is widely used in signal processing. The coefficients of AR model can be easily obtained by a LMS prediction error filter. However, it is known that such filter will give bias coefficients when the input signal is corrupted by noise. We proposes a new type of filter for adaptive AR modeling. It is shown that the new filter can converge to the Wiener solution without bias. Simulations are provided to demonstrate the results of the new filter
Keywords :
Gaussian noise; adaptive filters; adaptive signal processing; autoregressive processes; filtering theory; prediction theory; white noise; AR model coefficients; Gaussian white noise; LMS prediction error filter; Wiener solution; adaptive AR modeling; adaptive filter; bias coefficients; noise corrupted input signal; signal processing; simulations; Adaptive filters; Equations; Gaussian noise; Information filtering; Information filters; Least squares approximation; Noise figure; Predictive models; Resonance light scattering; White noise;
Conference_Titel :
Singapore ICCS '94. Conference Proceedings.
Print_ISBN :
0-7803-2046-8
DOI :
10.1109/ICCS.1994.474074
