LMS ITERATIVE ALGORITHMS APPLIED TO THE COMPUTATION OF TV GHOST CANCELER PARAMETERS

In this paper, three iterative forms of the LMS learning algorithm wer e tested for the calculation of the coefficients of FIR filters used a s TV Ghost Cancellers. These computational forms are: the Stochastic G radient Fixed-Step (SGLMS) [1] and a Variable Step (SLS-CD), [2] algor ithms, as well as the Recursive Modified Gram-Schmidt RMGS algorithm [ 3]. Because of the iterative nature of the selected algorithms, they a re very convenient to be used in on-line LTF filter coefficient adapta tions. This makes it possible to compute the coefficient values of the ghost canceller, when the sampling of the signal generates a huge amo unt of data, which is very hard to be handled with a PC. The aforement ioned algorithms are written in a very powerful and flexible matrix or iented software, and all the tests were performed using a very flexibl e TV System Simulator [4]. During the tests, fast convergence of the g host canceller coefficients to the theoretical values [4] have been ob served.