Title :
Adaptive FIR filtering based on minimum L∞-norm
Author :
Cho, Sung Ho ; Kim, Young Soo ; Cadzow, James A.
Author_Institution :
ETRI, Daejeon, South Korea
Abstract :
The authors present an efficient adaptive transversal filtering algorithm that is based on the minimum L∞-norm method. One of the significant contributions of the algorithm is that it provides less computational complexity than the competing normalized least mean square (NLMS) algorithm, yet retains the same motivation as the NLMS algorithm. The performance of this approach, however, is slightly worse than that in the mean-squared sense. It is shown how this algorithm is formulated by the minimum L∞-norm criterion in the hyperplane. Under the assumption that signals involved are zero-mean and Gaussian, and further employing the independence assumption, the authors then derive a set of nonlinear difference equations that characterize the mean and mean-squared behavior of the filter coefficients
Keywords :
adaptive filters; computational complexity; difference equations; digital filters; filtering and prediction theory; Gaussian signals; adaptive FIR filter; adaptive transversal filtering algorithm; computational complexity; filter coefficients; hyperplane; independence assumption; mean-squared behavior; minimum L∞-norm method; nonlinear difference equations; zero-mean signals; Adaptive filters; Algorithm design and analysis; Convergence; Difference equations; Error correction; Estimation error; Filtering; Finite impulse response filter; H infinity control; Vectors;
Conference_Titel :
Communications, Computers and Signal Processing, 1991., IEEE Pacific Rim Conference on
Conference_Location :
Victoria, BC
Print_ISBN :
0-87942-638-1
DOI :
10.1109/PACRIM.1991.160821