A Kernel Least Mean Square Algorithm Based on Randomized Feature Networks

A Kernel Least Mean Square Algorithm Based on Randomized Feature Networks

To construct an online kernel adaptive filter in a non-stationary environment, we propose a randomized feature networks-based kernel least mean square (KLMS-RFN) algorithm. In contrast to the Gaussian kernel, which implicitly maps the input to an infinite dimensional space in theory, the randomized...

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Bibliographic Details
Main Authors: Yuqi Liu, Chao Sun, Shouda Jiang
Format: Article
Language:English
Published: MDPI AG 2018-03-01
Series:Applied Sciences
Subjects:
kernel adaptive filter
KLMS algorithm
randomized feature networks
explicit feature mapping
mean square convergence
Online Access:http://www.mdpi.com/2076-3417/8/3/458

Internet

http://www.mdpi.com/2076-3417/8/3/458

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