Abstract
Three iterative forms of the LMS learning algorithm were tested for the calculation of the coefficients of FIR filters used as TV ghost cancellers. These computational forms are: the stochastic gradient fixed-step (SGLMS) and a variable step (SLS-CD), algorithms, as well as the recursive modified Gram-Schmidt RMGS algorithm. Because of the iterative nature of the selected algorithms, they are very convenient to be used in on-line LTF filter coefficient adaptations. This makes it possible to compute the coefficient values of the ghost canceller, when the sampling of the signal generates a huge amount of data, which is very hard to be handled with a PC. The aforementioned algorithms are written in a very powerful and flexible matrix oriented software, and all the tests were performed using a very flexible TV system simulator. During the tests, fast convergence of the ghost canceller coefficients to the theoretical values have been observed.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call