The presence of strong acoustic feedback degrades the convergence speed of the active noise control (ANC) filter, and in the worst case the ANC system may become unstable. A fixed feedback neutralization filter, obtai...
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The presence of strong acoustic feedback degrades the convergence speed of the active noise control (ANC) filter, and in the worst case the ANC system may become unstable. A fixed feedback neutralization filter, obtained offline, can be used to neutralize the acoustic feedback. The feedback path, however, may be time varying, and we may need continual adjustments during online operation of the ANC system. This paper proposes a new method for online modeling of the acoustic feedback path in ANC systems. The proposed method uses three adaptive filters;a noise control filter, a feedback path modeling (FBPM) filter, and an adaptive noise cancelation (ADNC) filter. The objective of ADNC filter is to remove the disturbance from the desired response of FBPM filter. In comparison with the existing method, which works only for predicable noise sources, the proposed method can work, as well, with the broadband noise sources. The computer simulations are carried out for narrowband (predictable) (case 1) and broadband (random) noise sources (case II). It is demonstrated that the proposed method performs better than the existing method in both cases.
In this paper, a novel adaptive energy and spectrum efficient inverse power control method that is based on the truncated filtered-x LMS (fxlms) algorithm is introduced. By truncated power control we mean power contro...
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ISBN:
(纸本)9781424408146
In this paper, a novel adaptive energy and spectrum efficient inverse power control method that is based on the truncated filtered-x LMS (fxlms) algorithm is introduced. By truncated power control we mean power control where transmission is interrupted if the channel state deteriorates to bad enough. Inverse power control minimizes the interference that a cognitive radio (CR) creates to licensed users and allows more users to share the spectrum. To further reduce the transmission power and consequently the interference, truncation in power control is used. The performance of the system is improved and the amount of needed transmitted energy is smaller. Based on numerical analysis this new method offers energy efficient transmission, helps to minimize interference to the primary users, and allows even more users to share the same spectrum.
An improved algorithm is presented to identify the secondary path based on the adaptive notch filter approach. Since the interference from the narrow band excitation signal is suppressed by the adaptive notch filter, ...
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An improved algorithm is presented to identify the secondary path based on the adaptive notch filter approach. Since the interference from the narrow band excitation signal is suppressed by the adaptive notch filter, the convergent speed of the on-line control path identification process is significantly improved. As a result, the controller performance is greatly enhanced. Besides the algorithm development, some important factors, such as the influence of reference signal on the controller convergent speed, are also discussed. The effectiveness of the algorithm is verified by experimental results.
This paper proposes a new method for online secondary path modeling in active noise control systems. The existing methods for active noise control systems with online secondary path modeling consist of three adaptive ...
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This paper proposes a new method for online secondary path modeling in active noise control systems. The existing methods for active noise control systems with online secondary path modeling consist of three adaptive filters. The main feature of the proposed method is that it uses only two adaptive filters. In the proposed method, the modified-fxlms (Mfxlms) algorithm is used in adapting the noise control filter and a new variable step size (VSS) least mean square (LMS) algorithm is proposed for adaptation of the secondary path modeling filter. This VSS LMS algorithm is different from the normalized-LMS (NLMS) algorithm, where the step size is varied in accordance with the power of the reference signal. Here, on the other hand, the step size is varied in accordance with the power of the disturbance signal in the desired response of the modeling filter. The basic idea of the proposed VSS algorithm stems from the fact that the disturbance signal in the desired response of the modeling filter is decreasing in nature, (ideally) converging to zero. Hence, a small step size is used initially and later its value is increased accordingly. The disturbance signal, however, is not available directly, and we propose an indirect method to track its variations. Computer simulations show that the proposed method gives better performance than the existing methods. This improved performance is achieved at the cost of a slightly increased computational complexity.
In the case of single-channel ANC systems, the reference signal is picked up by a reference microphone, and the "antinoise" is generated by a canceling loudspeaker. This antinoise signal propagates downstrea...
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ISBN:
(纸本)9781424407941
In the case of single-channel ANC systems, the reference signal is picked up by a reference microphone, and the "antinoise" is generated by a canceling loudspeaker. This antinoise signal propagates downstream to cancel the unwanted noise. However it also propagates upstream and corrupts the reference signal. This is called acoustic feedback. The presence of strong acoustic feedback degrades the convergence speed and in worst case the ANC system may become unstable. In this paper, we proposed modified method for improved performance. The computer simulations are carried out, which demonstrate the effectiveness of the proposed method, in comparison with the existing methods.
A selection detector in adaptive algorithm with weight constrained method for active noise control (ANC) is presented in this paper. Imposing weight constraints to the adaptation of the adaptive filter will effectivel...
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ISBN:
(纸本)0780394836
A selection detector in adaptive algorithm with weight constrained method for active noise control (ANC) is presented in this paper. Imposing weight constraints to the adaptation of the adaptive filter will effectively avoid over-updated phenomenon, such as a large movement of microphone or the sudden variations of the surrounding environment. It can be easily added in the adaptive procedure and will not burden heavily with complex computation. The selection of the weight constraint factor is prominent because a large weight constraint factor gives less constraint to the update of adaptive filter, whereas a small weight constraint factor may cause constraint of the update strictly. The selection detector is proposed to reduce the seeking time of weight constrained factors by imposing weight constraints to allocate the adaptive filter to effectively avoid over-updates phenomenon when there is a sudden large change in the original signal. From the selection detector block, these three weight constraint factors can be chosen appropriately to the minimum values of mean square error. The analysis gives useful information about preventing the adaptation from updating by the wrong learning and the robustness of the entire ANC system is improved in this paper. The results are verified to show the effectiveness through the computer simulations in this paper.
This paper proposes a new structure for feedforward active noise control (ANC) systems with online secondary path modeling. The proposed method: 1) uses the same error signal for updating the noise control process as ...
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This paper proposes a new structure for feedforward active noise control (ANC) systems with online secondary path modeling. The proposed method: 1) uses the same error signal for updating the noise control process as used for the secondary path modeling process and 2) incorporates an adaptive filtering with averaging based filtered-reference algorithm in the noise control process. The computer simulations have been conducted with both narrowband and broadband noise signals. It is shown that in the proposed ANC system the residual noise signal and the secondary-path-modeling error can be reduced at a faster convergence rate than the existing methods. This improved performance is achieved at the expense of a slightly increased computational complexity.
This letter proposes an adaptive filtering with averaging-based algorithm for active noise control (ANC) systems. This algorithm uses a similar structure as that of the fxlms-based ANC system. The proposed algorithm, ...
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This letter proposes an adaptive filtering with averaging-based algorithm for active noise control (ANC) systems. This algorithm uses a similar structure as that of the fxlms-based ANC system. The proposed algorithm, called Filtered-x Adaptive Filtering with Averaging (FxAFA) algorithm, uses averages of both data and correction terms to find the updated values of the tap weights of the ANC controller. The computer simulations are conducted for single-channel feedforward ANC systems. It is shown that the proposed algorithm gives fast convergence as compared with the fxlms algorithm and achieves better performance in the presence of the measurement noise. The comparison with the FxRLS algorithm shows that the proposed FxAFA algorithm is a better choice for low computational complexity and stable performance.
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