An adaptive algorithm for fast identification of FIR systems

In this paper, we develop a fast recursive algorithm with a view to finding the total least squares (TLS) solution for adaptive FIR filtering with input and output noises. We introduce a novel but approximate inverse power iteration in combination with Galerkin method so that the TLS solution can be updated adaptively at a lower computational cost. We further reduce the computational complexity of the developed algorithm by making efficient computation of the fast gain vector. We then make a careful investigation into global convergence of the developed algorithm. Simulation results are provided that clearly illustrate appealing performances of the developed algorithm.