Convergence models for lattice joint process estimators and least squares algorithms

A simple model characterizing the convergence properties of an adaptive digital lattice filter using gradient algorithms has been reported [1]. This model is extended to the least mean square (LMS) lattice joint process estimator [5], and to the least squares (LS) lattice and "fast" Kalman algorithms [9] -[16]. The models in each case are compared with computer simulation. The single-stage LMS lattice analysis presented in [1] is also applied to the LS lattice. Results indicate that for stationary inputs, the LMS lattice and LS algorithms exhibit similar behavior.