Title :
Comparison of least mean fourth and least mean square tracking
Author_Institution :
Nat. Knowledge Center, Abu Dhabi, United Arab Emirates
Abstract :
The paper provides new results concerning the tracking performance of the least mean fourth algorithm in comparison with that of the least mean square algorithm. The analysis is done in the context of tracking a Markov plant with a white Gaussian input. The comparison is done in terms of the minimum mean square deviation attained by each algorithm over the stability range of its step-size. Gaussian, uniform, and binary distributions of the plant noise are considered. Conditions that make one algorithm outperform the other are determined. Analytical results are supported by simulations.
Keywords :
Gaussian distribution; adaptive filters; least mean squares methods; Gaussian distribution; Markov plant; binary distribution; least mean fourth algorithm; least mean square algorithm; least mean square tracking; minimum mean square deviation; step-size; tracking performance; uniform distribution; white Gaussian input;
Conference_Titel :
Signals, Systems and Computers (ASILOMAR), 2012 Conference Record of the Forty Sixth Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
978-1-4673-5050-1
DOI :
10.1109/ACSSC.2012.6489119
