In this paper, a real time implementation of an active noise control (ANC) system for snoring cancellation is presented. This method is based on an online secondary path estimation procedure and includes a subband adaptive filtering (SAF) structure for the primary path estimation. The introduction of the SAF approach allows to improve the performances on the estimation of both primary and secondary path in terms of convergence rate. The algorithm has been compared with the state of the art through several experiments that have proved the effectiveness of the proposed system in real applications.

A real time subband implementation of an active noise control system for snoring reduction / Nobili, S.; Bruschi, V.; Bettarelli, F.; Cecchi, S.. - In: ISPA. - ISSN 1845-5921. - ELETTRONICO. - 2021-:(2021), pp. 109-114. (Intervento presentato al convegno 12th International Symposium on Image and Signal Processing and Analysis, ISPA 2021 tenutosi a hrv nel 2021) [10.1109/ISPA52656.2021.9552038].

A real time subband implementation of an active noise control system for snoring reduction

Nobili S.;Bruschi V.;Cecchi S.
2021-01-01

Abstract

In this paper, a real time implementation of an active noise control (ANC) system for snoring cancellation is presented. This method is based on an online secondary path estimation procedure and includes a subband adaptive filtering (SAF) structure for the primary path estimation. The introduction of the SAF approach allows to improve the performances on the estimation of both primary and secondary path in terms of convergence rate. The algorithm has been compared with the state of the art through several experiments that have proved the effectiveness of the proposed system in real applications.
2021
978-1-6654-2639-8
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/298335
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