Time-frequency analysis using AR models with variable forgetting factors

A method for estimating time-frequency representations of nonstationary signals using recursive least squares (RLS) with variable forgetting factors is described. The variable forgetting factor is adapted to a nonstationary signal by an extended prediction error criterion which accounts for the nonstationarity of the signal. This method has good adaptability in the nonstationary situation and low variance in the stationary situation.<>