Bursting in the LMS Algorithm

IEEE Transactions on Signal Processing

Volumn 43, Issue 10, 1995, Pages 2414-2417

  Rupp, Markus ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CHEBYSHEV APPROXIMATION; CONVERGENCE OF NUMERICAL METHODS; INVARIANCE; LAPLACE TRANSFORMS; LEAST SQUARES APPROXIMATIONS; MATRIX ALGEBRA; PROBABILITY; RANDOM PROCESSES; SIGNAL THEORY; VECTORS;

BURSTING; LAPLACE DENSITY; LEAST MEAN SQUARE ALGORITHMS; PROBABILITY OF FAILURE; SPHERICALLY INVARIANT RANDOM PROCESSES; TCHEBYCHEFF INEQUALITY; WEIGH ERROR VECTOR;

ALGORITHMS;

EID: 0029392152     PISSN: 1053587X     EISSN: 19410476     Source Type: Journal    
DOI: 10.1109/78.469846     Document Type: Article

References (8)

1. A. H. Sayed and M. Rupp, “On the robustness, convergence, and minimax performance of instantaneous-gradient adaptive filters,” in Proc. Asilomar Conf, Oct. 1994.
2. S. Haykin, A daptive Filter Theory. Englewood Cliffs, NJ: Prentice-Hall, 1991.
3. A. Papoulis, Probability, Random Variables, and Stochastic Processes. New York: McGraw Hill, 1987.
4. I. S. Gradshteyn and I. M. Ryzhik, Table of Integrals, Series and Products,. New York: Academic, 1980.
5. H. Brehm, “Description of spherically invariant random processes by means of G-functions,” Springer Lecture Notes in Mathematics, vol. 969, pp. 39-73, 1982.
6. H. Brehm and W. Stammler, “Description and generation of spherically invariant speech-model signals,” Signal Processing, vol. 12, no. 2, pp. 119-141, 1987.
7. M. Rupp, “The behavior of LMS and NLMS algorithms in the presence of spherically invariant processes,” IEEE Trans. Signal Processing, vol. 41. no. 3, pp. 1149-1160, Mar. 1993.
8. M. Rupp and R. Frenzel, “The behavior of LMS and NLMS algorithms with delayed coefficient update in the presence of spherically invariant processes,” IEEE Trans. Signal Processing, vol. 42, no. 3, pp. 668-672, Mar. 1994.