A new normalized minimum-error entropy algorithm with reduced computational complexity

Author

Bhotto, Md Zulfiquar Ali ; Antoniou, Andreas

Author_Institution

Dept. of Electr. & Comput. Eng., Univ. of Victoria, Victoria, BC, Canada

fYear

2009

fDate

24-27 May 2009

Firstpage

2561

Lastpage

2564

Abstract

A new normalized minimum-error entropy (NMEE) algorithm is proposed as an alternative to the minimum-error entropy (MEE) and the minimum-error entropy with self-adjusting step size (MEE-SAS) algorithms. The proposed NMEE algorithm requires fewer iterations and less computation to converge and yields lower misadjustment as compared to those of the MEE and the MEE-SAS algorithms.

Keywords

adaptive filters; computational complexity; convergence of numerical methods; mean square error methods; minimum entropy methods; NMEE; adaptive filter; computational complexity; mean square error method; minimum-error entropy-with-self adjusting step size algorithm; normalized minimum-error entropy algorithm; numerical convergence; Adaptive filters; Computational complexity; Convergence; Entropy; Higher order statistics; Kernel; Noise robustness; Quantization; Statistical distributions; Stochastic processes; Adaptive filters; MEE algorithms with self-adjusting step size; minimum-error entropy (MEE) algorithms; normalized MEE algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 2009. ISCAS 2009. IEEE International Symposium on

Conference_Location

Taipei

Print_ISBN

978-1-4244-3827-3

Electronic_ISBN

978-1-4244-3828-0

Type

conf

DOI

10.1109/ISCAS.2009.5118324

Filename

5118324