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Keywords = multichannel active noise control (ANC)

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17 pages, 4371 KiB  
Article
Adaptive Filtered-x Least Mean Square Algorithm to Improve the Performance of Multi-Channel Noise Control Systems
by Maha Yousif Hasan, Ahmed Sabah Alaraji, Amjad J. Humaidi and Huthaifa Al-Khazraji
Math. Comput. Appl. 2025, 30(4), 84; https://doi.org/10.3390/mca30040084 - 5 Aug 2025
Viewed by 259
Abstract
This paper proposes an optimized control filter (OCF) based on the Filtered-x Least Mean Square (FxLMS) algorithm for multi-channel active noise control (ANC) systems. The proposed OCF-McFxLMS algorithm delivers three key contributions. Firstly, even in difficult noise situations such as White Gaussian, Brownian, [...] Read more.
This paper proposes an optimized control filter (OCF) based on the Filtered-x Least Mean Square (FxLMS) algorithm for multi-channel active noise control (ANC) systems. The proposed OCF-McFxLMS algorithm delivers three key contributions. Firstly, even in difficult noise situations such as White Gaussian, Brownian, and pink noise, it greatly reduces error, reaching nearly zero mean squared error (MSE) values across all Microphone (Mic) channels. Secondly, it improves computational efficiency by drastically reducing execution time from 58.17 s in the standard McFxLMS algorithm to just 0.0436 s under White Gaussian noise, enabling real-time noise control without compromising accuracy. Finally, the OCF-McFxLMS demonstrates robust noise attenuation, achieving signal-to-noise ratio (SNR) values of 137.41 dB under White Gaussian noise and over 100 dB for Brownian and pink noise, consistently outperforming traditional approaches. These contributions collectively establish the OCF-McFxLMS algorithm as an efficient and effective solution for real-time ANC systems, delivering superior noise reduction and computational speed performance across diverse noise environments. Full article
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18 pages, 4347 KiB  
Article
The Effectiveness of Least Mean Squared-Based Adaptive Algorithms for Active Noise Control System in a Small Confined Space
by Francesco Mori, Andrea Santoni, Patrizio Fausti, Francesco Pompoli, Paolo Bonfiglio and Pietro Nataletti
Appl. Sci. 2023, 13(20), 11173; https://doi.org/10.3390/app132011173 - 11 Oct 2023
Cited by 2 | Viewed by 1965
Abstract
Active noise control (ANC) is a technique applied to eliminate an unwanted sound by superposing a signal of equal amplitude and opposite phase, sometimes defined as an anti-noise signal, computed through an adaptive algorithm. The study described herein aims to evaluate and compare [...] Read more.
Active noise control (ANC) is a technique applied to eliminate an unwanted sound by superposing a signal of equal amplitude and opposite phase, sometimes defined as an anti-noise signal, computed through an adaptive algorithm. The study described herein aims to evaluate and compare the performance of some of the most popular algorithms based on the least mean squares (LMS) approach applied to a multichannel active noise control system in a small, enclosed space. The comparison is conducted through an experimental evaluation of the ANC algorithms’ performance, carried out on a tractor cabin in a hemi-anechoic chamber, generating the unwanted sound field using a dodecahedron sound source placed outside the enclosure, emitting narrowband and broadband signals. The experimental analysis and the comparison with the results obtained in a free field condition have made it possible to show certain practical limitations when implementing the algorithms. The results show that the feed-forward systems allow for greater stability, avoiding the acoustic feedback from the control loudspeakers to the reference microphone when this is outside the cabin, while the feedback system is the slowest configuration to converge, requiring an internal modeling of the reference signal. With random signals, the feed-forward systems concentrate their performance in the range above 500 Hz, while the feedback system becomes ineffective. Full article
(This article belongs to the Special Issue Active Vibration and Noise Control)
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20 pages, 5207 KiB  
Article
Leaky Partial Update LMS Algorithms in Application to Structural Active Noise Control
by Dariusz Bismor
Sensors 2023, 23(3), 1169; https://doi.org/10.3390/s23031169 - 19 Jan 2023
Cited by 10 | Viewed by 2364
Abstract
Adaptive signal processing algorithms play an important role in many practical applications in diverse fields, such as telecommunication, radar, sonar, multimedia, biomedical engineering and noise control. Recently, a group of adaptive filtering algorithms called partial update adaptive algorithms (partial updates) has gathered considerable [...] Read more.
Adaptive signal processing algorithms play an important role in many practical applications in diverse fields, such as telecommunication, radar, sonar, multimedia, biomedical engineering and noise control. Recently, a group of adaptive filtering algorithms called partial update adaptive algorithms (partial updates) has gathered considerable attention in both research and practical applications. This paper is a study of the application of PUs to very demanding, structural active noise control (ANC) systems, which are of particular interest due to their ability to provide for a global noise reduction. However, such systems are multichannel, with very high computational power requirements, which may be reduced by the application of partial updates. The paper discusses the modifications necessary to apply PUs in structural ANC systems and the potential computational power savings offered by this application. As a result, leaky versions of the PU LMS algorithms are introduced to the general public. The paper also presents two simulation examples, based on real laboratory setups, confirming high performance of the proposed algorithms. Full article
(This article belongs to the Special Issue Detection and Feature Extraction in Acoustic Sensor Signals)
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13 pages, 4248 KiB  
Review
Some Practical Acoustic Design and Typical Control Strategies for Multichannel Active Noise Control
by Yijing Chu, Ming Wu, Hongling Sun, Jun Yang and Mingyang Chen
Appl. Sci. 2022, 12(4), 2244; https://doi.org/10.3390/app12042244 - 21 Feb 2022
Cited by 14 | Viewed by 3619
Abstract
Active noise control (ANC) systems usually involve a large number of loudspeakers and error microphones in order to achieve noise reduction over an extended region of space. Although fundamentals of ANC theory and principles of ANC methods have been well-established over the past [...] Read more.
Active noise control (ANC) systems usually involve a large number of loudspeakers and error microphones in order to achieve noise reduction over an extended region of space. Although fundamentals of ANC theory and principles of ANC methods have been well-established over the past 40 years, applications of this technology are facing new challenges. A larger quiet zone with better noise reduction performance is always desirable in a variety of real-life scenarios. This paper presents several important factors that affect the performance of multichannel ANC systems in some popular applications such as windows with natural ventilation and quiet-zone around heads. The factors affecting acoustic design include the reflection of a baffle plate, arrangement of error sensors in open areas, and so on. In addition, different control strategies are compared and analyzed, including centralized, decentralized, and distributed strategies. All these strategies are discussed from the signal processing side, which should be considered after a proper acoustic design. One of the important aims of this paper is to provide practical guidance for acoustic design and discuss several typical control strategies for multichannel ANC systems. Full article
(This article belongs to the Special Issue Application of Active Noise and Vibration Control)
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15 pages, 4680 KiB  
Article
A Hybrid Active Noise Control System for the Attenuation of Road Noise Inside a Vehicle Cabin
by Zibin Jia, Xu Zheng, Quan Zhou, Zhiyong Hao and Yi Qiu
Sensors 2020, 20(24), 7190; https://doi.org/10.3390/s20247190 - 15 Dec 2020
Cited by 37 | Viewed by 4596
Abstract
This paper proposed a local active control method for the reduction of road noise inside a vehicle cabin. A multichannel simplified hybrid active noise control (sHANC) system was first developed and applied to the rear left seat of a large sport utility vehicle [...] Read more.
This paper proposed a local active control method for the reduction of road noise inside a vehicle cabin. A multichannel simplified hybrid active noise control (sHANC) system was first developed and applied to the rear left seat of a large sport utility vehicle (SUV). The attenuation capability of the sHANC system was investigated through simulations, using reference signals provided by accelerometers on the suspensions and bodywork of the vehicle and microphones on the floor of cabin, respectively. It was shown that compared to the traditional feedforward system, the sHANC system using either vibrational or acoustical reference signals can produce a significant suppression of the narrowband peak noise between 75 and 80 Hz, but the system lost the control capability in a range of 100–500 Hz when the acoustic signals were used as references. To reduce the practical implementation costs while maintaining excellent reduction performance, a modified simplified hybrid ANC (msHANC) system was further proposed, in which combined vibrational and acoustical signals were used as reference signals. The off-line analyses showed that four reference accelerometers can be substituted by ten microphones without compromising attenuation performance, with 3.7 dBA overall noise reduction being achieved. The effect of delays on the reduction performance of msHANC system was also investigated. The result showed that the msHANC system was more sensitive to the delays compared to the sHANC system if using only vibrational reference signals. Full article
(This article belongs to the Special Issue Sensors for Road Vehicles of the Future)
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11 pages, 2007 KiB  
Brief Report
A Time-Efficient Method for Determining an Optimal Scaling Factor and the Encoder Resolution in the Multichannel FXECAP-L Algorithm with Evolving Order for Active Noise Control
by Ángel A. Vázquez, Xochitl Maya, Juan G. Avalos, Giovanny Sánchez, Juan C. Sánchez, Hector M. Pérez and Gabriel Sánchez
Appl. Sci. 2019, 9(3), 560; https://doi.org/10.3390/app9030560 - 8 Feb 2019
Cited by 3 | Viewed by 2991
Abstract
Affine projection (AP) algorithms have demonstrated faster convergence speed than conventional least mean square (LMS) algorithms, thus providing an attractive solution in the active noise control (ANC) field. However, the AP algorithms demand high computational cost, restricting their practical use in real-time ANC [...] Read more.
Affine projection (AP) algorithms have demonstrated faster convergence speed than conventional least mean square (LMS) algorithms, thus providing an attractive solution in the active noise control (ANC) field. However, the AP algorithms demand high computational cost, restricting their practical use in real-time ANC applications. Recently, a multichannel filtered-x error-coded affine projection-like (FXECAP-L) algorithm with evolving order has been proposed to reduce the computational burden by maintaining the convergence speed of AP algorithms. In order to obtain an efficient and robust FXECAP-L algorithm with evolving order, the scaling factor and encoder resolution need to be adjusted manually, which is a time-consuming and costly effort that must be carried out by expert designers. To reduce these costs and efforts, we introduce, for the first time, a strategy for automatic adjustment of the scaling factor and encoder resolution that benefits the rapid development of practical ANC applications. To demonstrate its practical use, we applied the proposed strategy for controlling the noise in an acoustic duct. The practical results demonstrate the automatic adjustment of the FXECAP-L algorithm which maintains high convergence speed at the expense of a small compromise in terms of processing time. Full article
(This article belongs to the Special Issue Active and Passive Noise Control)
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17 pages, 5194 KiB  
Article
Exploiting the Underdetermined System in Multichannel Active Noise Control for Open Windows
by Jianjun He, Bhan Lam, Dongyuan Shi and Woon Seng Gan
Appl. Sci. 2019, 9(3), 390; https://doi.org/10.3390/app9030390 - 23 Jan 2019
Cited by 12 | Viewed by 3537
Abstract
Active noise control (ANC) is a re-emerging technique to mitigate noise pollution. To reduce the noise power in large spaces, multiple channels are usually required, which complicates the implementation of ANC systems. In this paper, we separate the multichannel ANC problem into two [...] Read more.
Active noise control (ANC) is a re-emerging technique to mitigate noise pollution. To reduce the noise power in large spaces, multiple channels are usually required, which complicates the implementation of ANC systems. In this paper, we separate the multichannel ANC problem into two subproblems, where the subproblem of computing the control filter is usually an underdetermined problem. Therefore, we could leverage the underdetermined system to simplify the ANC system without degrading the noise reduction performance. For a single incidence, we compare the conventional fully-coupled (pseudoinverse) multichannel control with the colocated (diagonal) control method and find that they can achieve equivalent performance, but the colocated control method is less computationally intensive. Furthermore, the underdetermined system presents an opportunity to control noise from multiple incidences with one common fixed filter. Both the full-rank and the overdetermined optimal control filters are realized. The performance of these control methods was analyzed numerically with the Finite Element Method (FEM) and the results validate the feasibility of the full-rank and overdetermined optimal control methods, where the latter could even offer more robust performance in more complex noise scenarios. Full article
(This article belongs to the Special Issue Active and Passive Noise Control)
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17 pages, 1441 KiB  
Article
Multichannel Feedforward Active Noise Control System with Optimal Reference Microphone SelectorBased on Time Difference of Arrival
by Kenta Iwai, Satoru Hase and Yoshinobu Kajikawa
Appl. Sci. 2018, 8(11), 2291; https://doi.org/10.3390/app8112291 - 19 Nov 2018
Cited by 13 | Viewed by 6180
Abstract
In this paper, we propose a multichannel active noise control (ANC) system with an optimal reference microphone selector based on the time difference of arrival (TDOA). A multichannel feedforward ANC system using upstream reference signals can reduce various noises such as broadband noise [...] Read more.
In this paper, we propose a multichannel active noise control (ANC) system with an optimal reference microphone selector based on the time difference of arrival (TDOA). A multichannel feedforward ANC system using upstream reference signals can reduce various noises such as broadband noise by arranging reference microphones close to noise sources. However, the noise reduction performance of an ANC system degrades when the noise environment changes, such as the arrival direction. This is because some reference microphones do not satisfy the causality constraint that the unwanted noise propagates to the control point faster than the anti-noise used to cancel the unwanted noise. To solve this problem, we propose a multichannel ANC system with an optimal reference microphone selector. This selector chooses the reference microphones that satisfy the causality constraint based on the TDOA. Some experimental results demonstrate that the proposed system can choose the optimal reference microphones and effectively reduce unwanted acoustic noise. Full article
(This article belongs to the Special Issue Active and Passive Noise Control)
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