Cognitive virtual sensing technique for feedforward active noise control
Cognitive virtual sensing technique for feedforward active noise control
The virtual sensing (VS) technique enables an active noise control (ANC) system to estimate the virtual error signal for control using remote monitoring microphones. However, instances where noise characteristics and primary paths exhibit variations lead to a noticeable decline in performance for the conventional VS technique. To address this challenge, we propose the cognitive VS technique in this paper. Its objective is to enhance VS performance by providing a more precise estimate of the error signal based on environmental cognition. Differing from the previous selective VS technique, the cognitive VS technique connects both the reference and monitoring microphones to a lightweight classifier. Hence, the cognitive VS technique has the capability to dynamically adjust the VS filter in accordance with the noise and environmental conditions identified by the classifier. Simulation results demonstrate that the cognitive VS technique surpasses conventional and selective VS techniques in terms of adaptivity and generalisation when noise characteristics change and primary paths are time-varying.
Xie, Rong
c236a271-fe47-4fdb-b1ed-2598ef36ed4d
Tu, Anqi
4c37c611-e60c-4c3a-baa5-6da9ada6fdc6
Shi, Chuang
c46f72bd-54c7-45ee-ac5d-285691fccf81
Elliott, Stephen
721dc55c-8c3e-4895-b9c4-82f62abd3567
Li, Huiyong
55372056-e82d-4ca8-93c3-88c7f9d4216c
Zhang, Le
c6064631-e6c7-4e75-9605-54651fed3177
Xie, Rong
c236a271-fe47-4fdb-b1ed-2598ef36ed4d
Tu, Anqi
4c37c611-e60c-4c3a-baa5-6da9ada6fdc6
Shi, Chuang
c46f72bd-54c7-45ee-ac5d-285691fccf81
Elliott, Stephen
721dc55c-8c3e-4895-b9c4-82f62abd3567
Li, Huiyong
55372056-e82d-4ca8-93c3-88c7f9d4216c
Zhang, Le
c6064631-e6c7-4e75-9605-54651fed3177
Xie, Rong, Tu, Anqi and Shi, Chuang
,
et al.
(2024)
Cognitive virtual sensing technique for feedforward active noise control.
In ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
IEEE.
5 pp
.
(doi:10.1109/ICASSP48485.2024.10446463).
Record type:
Conference or Workshop Item
(Paper)
Abstract
The virtual sensing (VS) technique enables an active noise control (ANC) system to estimate the virtual error signal for control using remote monitoring microphones. However, instances where noise characteristics and primary paths exhibit variations lead to a noticeable decline in performance for the conventional VS technique. To address this challenge, we propose the cognitive VS technique in this paper. Its objective is to enhance VS performance by providing a more precise estimate of the error signal based on environmental cognition. Differing from the previous selective VS technique, the cognitive VS technique connects both the reference and monitoring microphones to a lightweight classifier. Hence, the cognitive VS technique has the capability to dynamically adjust the VS filter in accordance with the noise and environmental conditions identified by the classifier. Simulation results demonstrate that the cognitive VS technique surpasses conventional and selective VS techniques in terms of adaptivity and generalisation when noise characteristics change and primary paths are time-varying.
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ICASSP24_CVS_v1.6
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Accepted/In Press date: 19 January 2024
e-pub ahead of print date: 18 March 2024
Venue - Dates:
2024 IEEE International Conference on Acoustics, Speech and Signal Processing, , Seoul, Korea, Republic of, 2024-04-14 - 2024-04-19
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Local EPrints ID: 486901
URI: http://eprints.soton.ac.uk/id/eprint/486901
PURE UUID: 710d16fa-60e9-4c8c-a450-8302de4c95ae
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Date deposited: 08 Feb 2024 17:36
Last modified: 02 May 2024 02:04
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Contributors
Author:
Rong Xie
Author:
Anqi Tu
Author:
Chuang Shi
Author:
Huiyong Li
Author:
Le Zhang
Corporate Author: et al.
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