LMS iterative algorithms applied to the computation of TV ghost canceller parameters

• Published in: IEEE transactions on consumer electronics 1994-08, Vol.40 (3), p.662-670
• Main Authors: Yong, A., Markhauser, C.P.
• Format: Article
• Language: English
• Subjects: Finite impulse response filter; Iterative algorithms; Least squares approximation; Power generation; Sampling methods; Signal generators; Software algorithms; Stochastic processes; Testing
• ISSN: 0098-3063; 1558-4127
• DOI: 10.1109/30.320855

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.< >