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ADAPTİF FİLTRELERDE GAUSS-SEIDEL ALGORİTMASININ STOKASTİK YAKINSAMA ANALİZİ

Stochastic Convergence Analysis of Gauss-Seidel Algorithm in Adaptive Filters

Journal Name:

  • Uludağ Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi

Publication Year:

  • 2005

Key Words:

Keywords (Original Language):

Author NameUniversity of AuthorFaculty of Author
Abstract (2. Language): 
In this article, deterministic and stochastic convergence analysis of Gauss-Seidel algorithm that is proposed for adjusting adaptive filter parameters in iterative manner is performed, and it is shown that it is an unbiased parameter estimator that gives the optimum solution for Normal equations.
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Abstract (Original Language): 
Bu makalede, adaptif filtre parametrelerinin iteratif olarak ayarlanmasında kullanmak için önerilen Gauss- Seidel algoritmasının deterministik ve stokastik yakınsama analizi yapılmıştır ve Normal denklemlerin optimum çözümünü veren yansız bir kestireç olduğu gösterilmiştir.
FULL TEXT (PDF): 
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  • 2
87-92
  • Turkish

REFERENCES

References: 

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2. Bouchard, M. and Albu, F. (2005) The Gauss-Seidel fast affine projection algorithm for multichannel active noise
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3), 107-123.
3. Farhang-Boroujeny, B. (1998) Adaptive Filters: Theory and Applications, John Wiley & Sons, Chicester.
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and London.
5. Haykin, S. (1991) Adaptive Filter Theory, 2nd Ed., Prentice-Hall, Englewood Cliffs, New Jersey.
6. Koçal, O. H. (1998) A new approach to least squares adaptive filtering, IEEE International Symposium on
Circuits and Systems, Monterey, California, 261-264.
7. Ng, T. M., Farhang-Boroujeny, B. and Garg, H. K. (2003) An accelerated Gauss-Seidel method for inverse
modeling, Signal Processing, 83(3), 517-529.

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