Analysis of the dynamics of a memoryless nonlinear gradient IIR adaptive notch filter

A nonlinear dynamical model of a memoryless nonlinear gradient IIR adaptive notch filter for estimating the frequency of a noisy sinusoid is derived. The model is verified through simulations, where simulated responses of the estimated frequency are compared with the responses obtained from the model with good agreement. Convergence properties of the filter are studied using the model, and maximum step sizes and initial frequency ranges for convergence are determined. The performance of the adaptive filter in tracking a time-varying signal frequency is also examined.

► Large-signal analysis of the adaptive IIR notch filter is performed.
► Dynamical model for the memoryless nonlinear gradient (MNG) algorithm is obtained.
► Model is highly complex; therefore analysis is based on graphical methods.
► Convergence analysis of the MNG algorithm shows that it is not globally convergent.
► Frequency tracking analysis for FM signals is performed