Self-learning active noise control

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Self-learning active noise control.

An important step for active noise control (ANC) systems to be practical is to develop model independent ANC (MIANC) systems that tolerate parameter variations in sound fields. Reliabilities and stabilities of many MIANC systems depend on results of online system identifications. Parameter errors due to system identifications may threaten closed-loop stabilities of MIANC systems. A self-learnin...

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1 Zbigniew Ogonowski, Silesian University of Technology, 44-100 Gliwice, Akademicka 16, Poland, [email protected] Abstract  The paper presents a concept of network-based learning of Active Noise Control (ANC) problems. Arguments motivating remote experimenting are given. It follows from the presentation that basic experiments can be done automatically using “remote design”. The mo...

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In many active noise control (ANC) applications, an online secondary path modelling method that uses a white noise as a training signal is required. This paper proposes a new feedback ANC system. Here we modified both the FxLMS and the VSS-LMS algorithms to raised noise attenuation and modelling accuracy for the overall system. The proposed algorithm stops injection of the white noise at the op...

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ژورنال

عنوان ژورنال: The Journal of the Acoustical Society of America

سال: 2008

ISSN: 0001-4966

DOI: 10.1121/1.2968700