Analysis of a quasi-Newton adaptive filtering algorithm

An algorithm for FIR adaptive filters based on the quasi-Newton class of optimization algorithms is analyzed. The results obtained are presented in terms of a series of theorems that demonstrate the stability of the algorithm, and the boundedness and positive definiteness of the estimated autocorrelation matrix of the input signal. Simulation results are them presented for fixed- and floating-point implementation which show that the proposed algorithm has comparable convergence speed and superior robustness relative to other known Newton-type algorithms.