Performance analysis of the self-orthogonalising adaptive lattice filter

This paper describes new self-orthogonalising adaptive lattice filter (SALF ) structures to enhance slow convergence rates caused by eigenvalue spread. Firstly, we propose the variable stepsize self-orthogonalising adaptive la ttice filtering (VSALF) structure to speed up the convergence rate of parti al correlation (PARCOR) coefficients. Secondly, the partial self-orthogonal ising adaptive lattice filtering (PSALF) structure is proposed in order to enhance the tracking ability for nonstationary environments. Moreover, the PSALF structure can reduce computational complexity whilst maintaining a fa st convergence rate. A performance analysis based on the convergence model of the lattice predictor is given in terms of mean-squared error and Varian ce of the PARCOR coefficient error. Computer simulations are undertaken to verify the performance and applicability of the proposed filter structures. (C) 2000 Elsevier Science B.V. All rights reserved.