An Adaptive Radial Basis Function Network algorithm for nonlinear channel equalization 


Vol. 30,  No. 3, pp. 141-146, Mar.  2005


PDF
  Abstract

The authors investigate the convergence speed problem of nonlinear adaptive equalization. Convergence constraints and time constant of radial basis function network using stochastic gradient (RBF-SG) algorithm is analyzed and a method of making time constant independent of hidden-node output power by using sample-by-sample node output power estimation is derived. The method for estimating the node power is to use a single-pole low-pass filter. It is shown by simulation that the proposed algorithm gives faster convergence and lower minimum MSE than the RBF-SG algorithm.

  Statistics
Cumulative Counts from November, 2022
Multiple requests among the same browser session are counted as one view. If you mouse over a chart, the values of data points will be shown.


  Cite this article

[IEEE Style]

N. y. Kim, "An Adaptive Radial Basis Function Network algorithm for nonlinear channel equalization," The Journal of Korean Institute of Communications and Information Sciences, vol. 30, no. 3, pp. 141-146, 2005. DOI: .

[ACM Style]

Nam yong Kim. 2005. An Adaptive Radial Basis Function Network algorithm for nonlinear channel equalization. The Journal of Korean Institute of Communications and Information Sciences, 30, 3, (2005), 141-146. DOI: .

[KICS Style]

Nam yong Kim, "An Adaptive Radial Basis Function Network algorithm for nonlinear channel equalization," The Journal of Korean Institute of Communications and Information Sciences, vol. 30, no. 3, pp. 141-146, 3. 2005.

Search
(IN TITLE, AUTHOR, ABSTRACT,KEYWORDS)

Advanced Search ▼

POPULAR KEYWORDS
(TOP 10 KEYWORDS)

Recent Publications
(LAST 3 YEARS)






pISSN : 1226 - 4717
eISSN : 2287 - 3880