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Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers (1994)
Pacific Grove, CA, USA
Oct. 31, 1994 to Nov. 2, 1994
ISSN: 1058-6393
ISBN: 0-8186-6405-3
pp: 592-596
A.H. Sayed , Dept. of Electr. & Comput. Eng., California Univ., Santa Barbara, CA, USA
M. Rupp , Dept. of Electr. & Comput. Eng., California Univ., Santa Barbara, CA, USA
ABSTRACT
The paper establishes several robustness, optimality, and convergence properties of the widely used class of instantaneous-gradient adaptive algorithms. The analysis is carried out in a purely deterministic framework and assumes no apriori statistical information. It starts with a simple Cauchy-Schwarz inequality for vectors in an Euclidean space and proceeds to derive local and global energy bounds that are shown here to highlight, as well as explain, several relevant aspects of this important class of algorithms.<>
INDEX TERMS
adaptive filters, adaptive signal processing, convergence of numerical methods, minimax techniques, filtering theory, error analysis
CITATION

A. Sayed and M. Rupp, "On the robustness, convergence, and minimax performance of instantaneous-gradient adaptive filters," Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers(ACSSC), Pacific Grove, CA, USA, 1995, pp. 592-596.
doi:10.1109/ACSSC.1994.471521
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