Adaptive Fourier Linear Combiner Based on Third Order Weight Iteration and Variable Step Size LMS Algorithm

Adaptive Fourier linear combiners can efficiently model sinusoidal signals. This paper proposes an adaptive Fourier linear combiner based on third order weight iteration and variable step size LMS algorithm. The algorithm first uses the third-order weight iteration formula to replace the traditional weight iteration, then obtains the desired signal by estimating the mean value of the autocorrelation of the error signal, and constructs a new step iteration by combining the estimation of the cross-correlation coefficient between the error signal and the input signal. Finally, the experimental simulation results show that the algorithm proposed in this paper improves the convergence speed and reduces the steady-state error, and can also be better applied in the field of biomedical engineering.