Active noise control using adaptive digital signal processing

Eriksson, L. J.; Allie, Mark C.; Bremigan, Cary D.; Greiner, Richard A.

doi:10.1109/icassp.1988.197177

Cited by 24 publications

(5 citation statements)

References 9 publications

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“…The algorithm needs to collect the noise information, update filter coefficients and generate inverse waveform. In addition to standard LMS, protection of overflow and reset of coefficient could be necessary when the input noise is very large [5]. So the performance of the hybrid ANC is achieved.…”

Section: C) Proposed Method-hybrid Anc (H-anc)mentioning

confidence: 99%

“…The system becomes very stable by using FIR filters to design W(z). But the convergence rate of this algorithm depends on the accuracy of secondary path estimation S(z) and if we use higher order filters, the speed of algorithm decreases [5]. The acoustic feedback presence is the major drawback of this algorithm.…”

Section: Figure 4: Fxlms Anc Modelmentioning

confidence: 99%

“…Figure 2 shows headset module. The oval shape represents a microphone [5]. There are two microphones are there on the headset--one is inside the headset and the other is outside the headset.…”

Section: Introductionmentioning

confidence: 99%

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An Effective Method for Active Noise Control

Kumar¹,

Reddy²

2015

CVRJST

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By introducing an "antinoise" wave through secondary sources the active noise control (ANC) is achieved. Through an electronic system, the secondary sources are connected using a specific signal processing algorithm for the particular cancellation method. In this paper, we propose a method which is combination of both Feed-forward and Feedback active noise control systems called Hybrid active noise control (H-ANC) method. This method uses lower order filters and also reduces distortion generated by the feedback ANC. So this method is relatively more stable than feedback ANC. The Computation requirements for Hybrid ANC would be high and real-time implementations during one cycle. The algorithm generate the inverse waveform of the signal by collecting the noise information and update the filter coefficients effectively.Keywords-Active noise canceling model, secondary path estimation, feed forward ANC technique, feedback ANC technique.

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Section: C) Proposed Method-hybrid Anc (H-anc)mentioning

confidence: 99%

Section: Figure 4: Fxlms Anc Modelmentioning

confidence: 99%

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An Effective Method for Active Noise Control

Kumar¹,

Reddy²

2015

CVRJST

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“…Since Hz(q-') is being estimated on-line, the resulting algorithm is thus much more robust than the existing ones [5]- [7] in that the relative positions of microphone 2 and the actuator do not affect the performance much.…”

Section: (3)mentioning

confidence: 99%

“…of speakers)] will have to be estimated manually for each installation. [7] used an auxiliary random noise generator which obviously increases costs and also introduces unnecessary noise into the output.…”

Section: (3)mentioning

confidence: 99%

Robust adaptive algorithms for active noise and vibration control

Fan

Vemuri

International Conference on Acoustics, Speech, and Signal Processing

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Most active noise and/or vibration control devices utilize some adaptive filters to estimate the transfer function (of the primary channel) from the noise source to a transducer at which point cancellation is to occur. However, another transfer function (of the auxiliary channel) from the actuator (including actuator characteristics) to the transducer is generally non-unity but has been often ignored. This paper describes new adaptive algorithms which simultaneously estimate and track the two transfer functions on-line. No random noise generator is required. Since both transfer functions are estimated and counted for, the resulting adaptive algorithms are much more robust than the existing ones in that moving the transducer and/or the actuator around does not affect the performance much. Real-time implementation results compare very favorably for one of our new algorithms in the sense of the robustness.

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The Design of Active Noise Control Systems for Compact and Distributed Sources

Tokhi

1999

Journal of Sound and Vibration

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Active noise control using adaptive digital signal processing

Cited by 24 publications

References 9 publications

An Effective Method for Active Noise Control

An Effective Method for Active Noise Control

Robust adaptive algorithms for active noise and vibration control

The Design of Active Noise Control Systems for Compact and Distributed Sources

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