Alternate Realizations to Adaptive IIR Filters and Properties of Their Performance Surfaces

Characteristics of the mean-square error surface in adaptive digital filters determine how well a gradient algorithm performs within a given filter structure, i.e., if the surface has steep slopes and contains local minima, a gradient algorithm will have difficulty reaching the global minimum. It is shown how different filter structures of an adaptive filter leads to a change in the characteristics of the corresponding error surface, and consequently, to a change in the corresponding convergence rate and minimum mean-square error.