Turkish Journal of Electrical Engineering and Computer Sciences, ( ISI ), Volume (25), No (25), Year (2017-7) , Pages (2606-2613)

Title : ( Application of reinforcement learning for active noise control )

Authors: S. A. HOSEINI SABZEVARI , Majid Moavenian ,

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Active noise control (ANC) systems are used to reduce the sound noise level by generating antinoise signals. M-Estimators are widely employed in ANC systems for updating the adaptive FIR lter taps used as the system controller. Observing the state-of-the-art M-estimators design shows that there is a need for further improvements. In this paper, a feedback ANC based on the reinforcement learning (RL) method is proposed. The sensitivity of the constant parameter in the RL method is checked. The effectiveness of the proposed method is proven by comparing the results with previous feedforward studies through computer simulations.

Keywords

, Active noise control, M-estimator, reinforcement
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@article{paperid:1064031,
author = {S. A. HOSEINI SABZEVARI and Moavenian, Majid},
title = {Application of reinforcement learning for active noise control},
journal = {Turkish Journal of Electrical Engineering and Computer Sciences},
year = {2017},
volume = {25},
number = {25},
month = {July},
issn = {1300-0632},
pages = {2606--2613},
numpages = {7},
keywords = {Active noise control; M-estimator; reinforcement learning},
}

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%0 Journal Article
%T Application of reinforcement learning for active noise control
%A S. A. HOSEINI SABZEVARI
%A Moavenian, Majid
%J Turkish Journal of Electrical Engineering and Computer Sciences
%@ 1300-0632
%D 2017

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