Title :
H∞ filtering for noise reduction using a total least squares estimation approach
Author :
Shimizu, Jun´ya ; Mitra, Sanjit K.
Author_Institution :
Dept. of Electr. & Comput. Eng., California Univ., Santa Barbara, CA, USA
Abstract :
A noise reduction algorithm for signals corrupted by additive unknown L2 white noise is proposed using an H∞ filtering framework. The proposed algorithm consists of two steps: a signal enhancement step and a parameter estimation step, which are iterated at each instant. To weaken the dependence between the signal enhancement step and the parameter estimation step, a total least squares estimation step for the dynamical model parameters needed in the H∞ filtering is introduced. The effectiveness of the proposed algorithm under low signal-to-noise ratio environments is demonstrated by simulation
Keywords :
Gaussian processes; H∞ optimisation; adaptive filters; adaptive signal processing; least mean squares methods; parameter estimation; recursive estimation; signal processing; white noise; AR parameters; H∞ filtering; SNR; adaptive algorithm; dynamical model parameters; iterative method; low signal-to-noise ratio; noise reduction algorithm; parameter estimation; signal enhancement; simulation; total least squares estimation; white Gaussian process; white noise; Filtering algorithms; Gaussian noise; Least squares approximation; Noise generators; Noise measurement; Noise reduction; Parameter estimation; Signal to noise ratio; White noise; Working environment noise;
Conference_Titel :
Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-4428-6
DOI :
10.1109/ICASSP.1998.681770
