Transform domain adaptive filtering algorithm via modified power estimator

This letter analyses the convergence behaviour of the transform domain leas t mean square (TDLMS) adaptive filtering algorithm which is based on a well known interpretation of the variable stepsize algorithm. With this interpr etation, the analysis is considerably simplified. The time varying stepsize is implemented by the modified power estimator to redistribute the spread power after transformation. The main contribution of this letter is the sta tistical performance analysis in terms of mean and mean squared error of th e weight error vector and the decorrelation property of the TDLMS is presen ted by the lower and upper bound of eigenvalue spread ratio. The theoretica l analysis results are validated by Monte Carlo simulation.