Title : ( A new modeling algorithm – Normalized Kernel Least Mean Square )
Authors: hamed modaghegh , Hossein Khosravi Roshkhari , saied ahoon manesh , Hadi Sadoghi Yazdi ,
Full TextAbstract
In this paper Normalized Kernel Least Mean Square (NKLMS) algorithm is presented which has applications in system modeling and pattern recognition. In 2007 a similar algorithm was proposed Named Kernel Least Mean Square (KLMS), and a modified version of KLMS was introduced in 2008. Although KLMS has good results in prediction of some time series, high sensitivity to step-size and signal amplitude stability, still remain as problems. In this paper NKLMS and its ability in prediction and identification of time series is presented and is compared to KLMS method. A variable named stepsize that was used in the algorithm has made NKLMS more efficient in prediction of time-series which have inconsistency in amplitude. Thus, convergence speed and system tracking are improved. Furthermore the proposed algorithm is applied to channel modeling.
Keywords
, Keywords— Least Mean Squar, System modeling, Pattern recognition, Time-Series Prediction
@inproceedings{paperid:1014132,
author = {Modaghegh, Hamed and Khosravi Roshkhari, Hossein and Ahoon Manesh, Saied and Sadoghi Yazdi, Hadi},
title = {A new modeling algorithm – Normalized Kernel Least Mean Square},
booktitle = {6th International Conference on Innovations in Information Technology 2009},
year = {2009},
location = {دبی},
keywords = {Keywords— Least Mean Squar; System modeling;
Pattern recognition; Time-Series Prediction},
}
%0 Conference Proceedings
%T A new modeling algorithm – Normalized Kernel Least Mean Square
%A Modaghegh, Hamed
%A Khosravi Roshkhari, Hossein
%A Ahoon Manesh, Saied
%A Sadoghi Yazdi, Hadi
%J 6th International Conference on Innovations in Information Technology 2009
%D 2009
