DocumentCode :
1260757
Title :
Transient Mean-Square Analysis of Prediction Error Method-Based Adaptive Feedback Cancellation in Hearing Aids
Author :
Maluenda, Yasmín Montenegro ; Bermudez, José Carlos M
Author_Institution :
Dept. of Electr. Eng., Univ. of Antofagasta, Antofagasta, Chile
Volume :
20
Issue :
1
fYear :
2012
Firstpage :
261
Lastpage :
275
Abstract :
Acoustic feedback is one of the main problems in modern hearing aids. It distorts the desired signal and limits the maximum stable gain. Results on acoustic feedback cancellation systems based on the prediction error method of closed-loop identification indicate that they perform better than most alternative solutions. Most available analyses of such systems, however, are limited to steady-state results. This paper presents a transient mean-square analysis of a recently proposed system. The structure is analyzed for slow adaptation and for autoregressive input signals. Analytical models are derived for the mean and mean-square adaptive weight behaviors. This includes a model for the transient behavior of the bias in the feedback path estimator. Monte Carlo simulations are presented to verify the accuracy of the derived models.
Keywords :
Monte Carlo methods; adaptive systems; autoregressive processes; closed loop systems; hearing aids; least mean squares methods; medical signal processing; Monte Carlo simulation; acoustic feedback cancellation system; adaptive feedback cancellation; analytical model; autoregressive input signal; closed loop identification; feedback path estimator; hearing aids; maximum stable gain; mean square adaptive weight behavior; prediction error method; slow adaptation; transient mean square analysis; Acoustics; Adaptation model; Adaptive systems; Analytical models; Auditory system; Hearing aids; Transient analysis; Adaptive systems; feedback cancellation; hearing aids; least mean square (LMS); statistical analysis;
fLanguage :
English
Journal_Title :
Audio, Speech, and Language Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1558-7916
Type :
jour
DOI :
10.1109/TASL.2011.2160852
Filename :
5934583
Link To Document :
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