DocumentCode :
3388533
Title :
Convergence Analysis of Hirschman Optimal Transform (HOT) LMS Adaptive Filter
Author :
Alkhouli, Osama ; DeBrunner, Victor E.
fYear :
2007
fDate :
26-29 Aug. 2007
Firstpage :
126
Lastpage :
130
Abstract :
We present a general convergence analysis of the recently introduced HOT LMS Adaptive filter and show that the autocorrelation matrix in the HOT domain is asymptotically Block diagonal and the HOT LMS adjusts the learning rate of each block to improve the convergence speed of the adaptive filter as compared to LMS. The theoretical findings were verified through numerical calculations and simulations.
Keywords :
Adaptive equalizers; Adaptive filters; Analytical models; Autocorrelation; Convergence; Energy measurement; Frequency measurement; Least squares approximation; Measurement uncertainty; Time measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Statistical Signal Processing, 2007. SSP '07. IEEE/SP 14th Workshop on
Conference_Location :
Madison, WI, USA
Print_ISBN :
978-1-4244-1198-6
Electronic_ISBN :
978-1-4244-1198-6
Type :
conf
DOI :
10.1109/SSP.2007.4301232
Filename :
4301232
Link To Document :
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