Model-free iterative learning control for repetitive impulsive noise using FFT
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part II
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To overcome the limitations of the existing algorithms for active impulsive noise control, an algorithm based on minimizing the squared logarithmic transformation of the error signal is proposed in this correspondence. The proposed algorithm is more robust for impulsive noise control and does not need the parameter selection and thresholds estimation according to the noise characteristics. These are verified by theoretical analysis and numerical simulations.