Eigenvalue equalization filtered-x (EE-FXLMS) algorithm applied to the active minimization of tractor noise in a mock cabin

Thomas, Jared J.; Lovstedt, Stephan P.; Blotter, Jonathan D.; Sommerfeldt, Scott D.; Faber, Ben

doi:10.3397/1.2835192

Cited by 8 publications

(6 citation statements)

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“…Thomas et al developed the EE-FXLMS algorithm in 2008 [17,18]. The basic configuration of the EE-FXLMS algorithm for vehicle powertrain response is shown in Figure 11.…”

Section: Ee-fxlms Algorithmmentioning

confidence: 99%

“…Thomas developed a relatively simpler structure, to improve the convergence behavior of the FXLMS algorithm. This algorithm is known as the eigenvalue equalization filtered-x least mean square (EE-FXLMS) algorithm [17,18]. The overall convergence behavior is greatly improved by flattening the magnitude response of the estimated secondary path, while leaving the phase unchanged.…”

Section: Introductionmentioning

confidence: 99%

“…The eigenvalue-equalization process, which is highlighted inFigure 11, can be used to reduce the dynamic range. It is implemented in the following steps[17]: Block diagram of the vehicle powertrain ANC system using the EE-FXLMS algorithm 1. Get the time-domain response ( ) of the secondary path through system identification.…”

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confidence: 99%

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Active control of vehicle powertrain noise using adaptive notch filter with inverse model LMS algorithm

Sun

Feng

et al. 2016

IJVNV

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“…Thomas et al developed the EE-FXLMS algorithm in 2008 [17,18]. The basic configuration of the EE-FXLMS algorithm for vehicle powertrain response is shown in Figure 11.…”

Section: Ee-fxlms Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Active control of vehicle powertrain noise using adaptive notch filter with inverse model LMS algorithm

Sun

Feng

et al. 2016

IJVNV

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“…Unfortunately, this approach would necessitate a more complex implementation that would require increased computational resources. In addition to the frequency domain and subband algorithms, Thomas et al 33 proposed an eigenvalue equalization algorithm to improve the convergence of the FXLMS algorithm. This algorithm utilizes a modified secondary path function in place of the actual secondary path model.…”

Section: Initial Testmentioning

confidence: 99%

Active control of magnetic resonance imaging response using inverse modeling

Li¹,

Rudd²,

Lim³

et al. 2011

Noise Control Eng. J.

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Magnetic resonance imaging (MRI), a procedure for medical diagnosis and biomedical research, generates significant levels of acoustic emissions during operation. The noise is normally dominated by clusters of harmonics throughout the audio spectrum. In this paper, an active noise control scheme using the inverse modeling technique is proposed and studied for pre-recorded MRI response obtained during the operation of a 4 T whole-body MRI scanner. The recorded MRI acoustic noise is played back through a high fidelity stereo system in a sound quality room and controlled using a headset equipped with the proposed active controller. The results demonstrate that noise reduction of over 20 dB is measured during the initial baseline test. Additional reduction is achieved by modifying the response of the secondary path, which extends the effective frequency range to 5 kHz. Results comparing convergence rates are also discussed. © 2011 Institute of Noise Control Engineering.

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“…While these approaches work, they either increase the complexity of the control algorithm or are only effective for specific applications. Recently, a new approach called the eigenvalue equalization filtered-x least mean square (EE-FXLMS) algorithm has been developed by Sommerfeldt et al [23][24][25][26]. The technique is designed to overcome the frequency-dependent performance problem.…”

Section: Introductionmentioning

confidence: 99%

Virtual Secondary Path Algorithm for Multichannel Active Control of Vehicle Powertrain Noise

Duan¹,

Li²,

Lim

et al. 2013

Journal of Vibration and Acoustics

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An enhanced multiple-input multiple-output (MIMO) filtered-x least mean square (FXLMS) algorithm using improved virtual secondary path is proposed as the basis for an active noise control (ANC) system for treating vehicle powertrain noise. This new algorithm is developed to overcome the limitation caused by the frequency-dependent property of the standard FXLMS algorithm and to reduce the variation of convergence speed inherent in multiple-channel cases, in order to improve the overall performance of the control system. In this study, the convergence property of the proposed algorithm is analyzed in the frequency domain in order to yield a better understanding of the physical meaning of the virtual secondary path. In practice, because of the arrangement and sensitivities of the actuators (speakers), transducers (microphones), and physical environment, the magnitude response of the main secondary paths can be very different from each other. This difference will cause difficulty in the overall convergence of the algorithm, which will result in minimal attenuation at some of the channels. The proposed channel equalized (CE) virtual secondary path algorithm is designed to tackle this difficulty by equalizing the mean magnitude level of the main secondary paths and by adjusting other secondary paths correspondingly to keep the coupling effects among the control channels unchanged. The performance of the proposed algorithm is validated by analyzing a two-input two-output active powertrain noise control system.

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Eigenvalue equalization filtered-x (EE-FXLMS) algorithm applied to the active minimization of tractor noise in a mock cabin

Cited by 8 publications

References 0 publications

Active control of vehicle powertrain noise using adaptive notch filter with inverse model LMS algorithm

Active control of vehicle powertrain noise using adaptive notch filter with inverse model LMS algorithm

Active control of magnetic resonance imaging response using inverse modeling

Virtual Secondary Path Algorithm for Multichannel Active Control of Vehicle Powertrain Noise

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