By Topic

Least-mean kurtosis: a novel higher-order statistics based adaptive filtering algorithm

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $31
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Tanrikulu, O. ; Dept. of Electr. Eng., Imperial Coll. of Sci., Technol. & Med., London ; Constantinides, A.G.

The least-mean kurtosis (LMK) adaptive FIR filtering algorithm is described which uses the negated kurtosis of the error signal as the cost function to be minimised. Unlike other higher-order statistics based adaptive algorithms, it is computationally efficient and it best suits those applications in which the noise contamination degrades the performance of the classical adaptive filtering algorithms

Published in:

Electronics Letters  (Volume:30 ,  Issue: 3 )