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Paper Information

Journal:   INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE (ENGLISH)   Winter 2003 , Volume 14 , Number 1; Page(s) 171 To 180.
 
Paper: 

ADAPTIVE HAMMERSTEINNORMALIZED LEAST-MEAN SQUARE FILTERIN

 
 
Author(s):  KAHAEI M.H.
 
* 
 
Abstract: 
While the Hammerstein expression is computationally attractive for modeling of nonlinear systems, the optimal calculation of filter coefficients is practically cumbersome. A proper solution to this problem is the use of adaptive algorithms. In this paper, the Hammerstein Normalized LMS algorithm is proposed by deriving the corresponding time varying optimal step-size parameter in a closed form. The convergence behavior of this algorithm is inspected using computer simulations. The results show that the proposed algorithm achieves a faster convergence speed compared to the Hammerstein LMS algorithm, practically at the cost of an acceptable increase in computations.
 
Keyword(s): HAMMERSTEIN SERIES, NLMS ALGORITHM, OPTIMAL STEP-SIZE PARAMETER
 
 
References: 
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Cite:
APA: Copy

KAHAEI, M. (2003). ADAPTIVE HAMMERSTEINNORMALIZED LEAST-MEAN SQUARE FILTERIN. INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE (ENGLISH), 14(1), 171-180. https://www.sid.ir/en/journal/ViewPaper.aspx?id=4958



Vancouver: Copy

KAHAEI M.H.. ADAPTIVE HAMMERSTEINNORMALIZED LEAST-MEAN SQUARE FILTERIN. INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE (ENGLISH). 2003 [cited 2021April14];14(1):171-180. Available from: https://www.sid.ir/en/journal/ViewPaper.aspx?id=4958



IEEE: Copy

KAHAEI, M., 2003. ADAPTIVE HAMMERSTEINNORMALIZED LEAST-MEAN SQUARE FILTERIN. INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE (ENGLISH), [online] 14(1), pp.171-180. Available at: <https://www.sid.ir/en/journal/ViewPaper.aspx?id=4958>.



 
 
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