LEAST-MEAN KURTOSIS - A NOVEL HIGHER-ORDER STATISTICS BASED ADAPTIVE FILTERING ALGORITHM

Authors
TANRIKULU O CONSTANTINIDES AG
Citation
O. Tanrikulu et Ag. Constantinides, LEAST-MEAN KURTOSIS - A NOVEL HIGHER-ORDER STATISTICS BASED ADAPTIVE FILTERING ALGORITHM, Electronics Letters, 30(3), 1994, pp. 189-190
Citations number
6
Categorie Soggetti
Engineering, Eletrical & Electronic
Journal title
Electronics Letters → ACNP
ISSN journal
00135194
Volume
30
Issue
3
Year of publication
1994
Pages
189 - 190
Database
ISI
SICI code
0013-5194(1994)30:3<189:LK-ANH>2.0.ZU;2-P
Abstract
The least-mean kurtosis (LMK) adaptive FIR filtering algorithm is desc ribed which uses the negated kurtosis of the error signal as the cost function to be minimised. Unlike other higher-order statistics based a daptive algorithms, it is computationally efficient and it best suits those applications in which the noise contamination degrades the perfo rmance of the classical adaptive filtering algorithms.