The Euclidean Direction Search algorithm in adaptive Filtering

摘要

A new class of least-squares algorithms is pre- sented for adaptive filtering. The idea is to use a foxed set of directions and perform line search with one direction at a time in a cyclic fashion. These algorithms are called Euclidean Direction Search (EDS)algorithms. The fast version of this class is called The Fast-EDS or FEDs algorithm. It is shown to have O(N) Computational complexity and a convergence rate comparable to That of the RLS algorithm. Computer simulations are presented To illustrate the performance of the new algorithm.