Variable-Step FXLMS algorithm for Active Noise Control based on signal prediction

In order to solve the problem that the convergence speed and convergence accuracy of FXLMS active noise reduction algorithm can not be achieved simultaneously due to the fixed step size, this paper proposes a variable step size FXLMS algorithm (PFXLMS) based on noise signal prediction. After reasonably choosing the length of noise signal sequence and fitting polynomial, the estimation of the noise signal at the next moment is obtained by fitting the initial noise signal with the least square method. so that the step size of the algorithm changes with the estimated value of noise signal at the next moment according to the characteristics of the arctangent function. To verify the performance of the PFXLMS, the noise of commercial blocks is collected and imported into MATLAB to carry out the simulation experiment of noise reduction using different algorithms. The simulation analysis shows that the proposed PFXLMS algorithm is superior to FXLMS algorithm and the variable step FXLMS algorithm based on arctangent function in both convergence speed and convergence accuracy.