A two-dimensional adaptive joint-process estimator using new lattice form

The present paper presents two-dimensional (2D) adaptive joint-process estimator using new lattice structure. The normalized LMS algorithm is used to update the filter coefficients. The proposed adaptive lattice estimator can represent a wide class of 2-D FIR systems and possesses orthogonality in the backward prediction error fields. These properties ensure superior convergence speed and tracking properties. Through computer simulation, the proposed model has been demonstrated to be useful for noise cancellation.