An Efficient Method to Regularize Refer- Ence Signal for Anc System

In this paper, an improved algorithm for active control of fan noise is proposed. The main idea behind this work is to optimize the components in the reference signal using the information from the unwanted fan noise. In the algorithm, the linear prediction coefficients obtained from the noise is used to build an autoregressive model. Then the model is applied to the reference signal to improve the correlation between the regularized reference signal and the noise. This reference signal regularization (RSR) is carried out automatically by an adaptive autoregressive process. The RSR improves the control performance noticeably. The algorithm has a fast convergence rate and high stability with a tolerant increase in computational complexity. It was implemented to reduce the noise from a real fan on a digital signal processor.