Iterative system modeling using multigrid techniques

New system identification algorithms utilizing multi-grid techniques are presented. System identification algorithms based on iterative methods are enhanced and made more efficient using the multigrid methods. The reduction in the number of iterations required to converge to a solution is realized by forcing the low frequency error components to appear to be at a higher frequency by transferring to a coarser sampling period. The iterations are performed at coarse sampling periods, and the results of convergence are transferred back to the original sampling periods. Results are presented for finite impulse response (FIR) and infinite impulse response (IIR) system identification problems