Noise Control, Reduction and Cancellation Solutions in by D. Siano

By D. Siano

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The tap-weights w a (n ) of the fractional Fourier domain adaptive filter are updated iteratively by (13) wa (n + 1) = wa (n ) + μxa,p (n )e∗ (n ). The FrFT parameter a should be estimated and kept updated during the adaptation process. 12 by LMS and NLMS algorithms without introducing the secondary path effects S(z). 12(a) shows the chirp-type primary noise in time domain. This signal is transformed to a sinusoidal signal by taking FrFT at the appropriate order. Then, adaptation procedure is employed.

15] W. S. Gan, Q. Z. Zhang, and Y. Zhou, “Adaptive recurrent fuzzy neural networks for active noise control,” Journal of Sound and Vibration, vol. 296, (2006), 935-948. Adaptive Fractional Fourier Filtering in Active Noise Control Adaptive Fractional Fourier Domain Filtering in Domain Active Noise Control 45 17 [16] X. Liu X. Li, Q. Z. Zhang, Y. Zhou, and W. S. Gan, “A nonlinear ANC system with a SPSA-based recurrent fuzzy neural network controller,” Lecture Notes in Computer Science, vol. 4491, 2007.

Zhang, Y. Zhou, and W. S. Gan, “A nonlinear ANC system with a SPSA-based recurrent fuzzy neural network controller,” Lecture Notes in Computer Science, vol. 4491, 2007. [17] Q. Z. Zhang and W. S. Gan, “Active noise control using a simplified fuzzy neural network,” Journal of Sound and Vibration, vol. 272,(2004), 437-449. [18] Q. Z. Zhang and W. S. Gan, A model predictive algorithm for active noise control with online secondary path modelling, Journal of Sound and Vibration, vol. 270, (2004), 1056-1066.

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