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Block diagram of the cascading ANC system for improving adaptation of FxLMS algorithm in the presence of uncorrelated disturbance v(n ) (Sun & Kuo, 2007). Since a disturbance free error signal is used, cascading ANC improves the convergence of the FxLMS algorithm. However, it cannot mitigate effect of the uncorrelated disturbance v(n ) from the residual noise eo (n ). One solution for ANC of correlated and uncorrelated disturbances would be to consider a hybrid ANC system comprising feedforward ANC W (z) and feedback ANC B (z) as shown in Fig.

2009a). Improving performance of FxLMS algorithm for active noise control of impulsive noise. Journal of Sound and Vibration, Vol. 327, No. 3–5. 2009, pp. 647–656. Akhtar, M. T. & Mitsuhashi, W. (2009b). Robust adaptive algorithms for active noise control of impulse noise. Proceedings of IEEE International Conference Acoustic Speech Signal Processing (ICASSP), pp. 261–264, April 19-24, 2009. Akhtar, M. T. & Mitsuhashi, W. (2011). Improving performance of hybrid active noise control systems for uncorrelated narrowband disturbances.

The development of robust and efficient online secondary path modeling algorithm, without requiring additive random noise, is critical and demands further research. The feedforward ANC system shown in Fig. 1 uses the reference microphone to pick up the reference noise x (n ), processes this input with an adaptive filter to generate an antinoise y(n ) to cancel primary noise acoustically in the duct, and uses an error microphone to measure the error e(n ) and to update the adaptive filter coefficients.

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