By Topic

Identification of Frequency-Hopping Spread Spectrum Signals Using SVMs with Wavelet Kernels

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 $13
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

3 Author(s)

This paper proposes a novel method of using wavelet kernel functions in Support Vector Machines (SVMs), and this method is applied to identification of individual communication transmitter which works in frequency-hopping spread spectrum modulation. The adoption of kernel function can improve the classification rate. The experimental results show how the recognition rates change with the parameters of wavelet kernel function. In a certain specific range, the classification rates maintain at a high level.

Published in:

Intelligent Systems and Applications (ISA), 2010 2nd International Workshop on

Date of Conference:

22-23 May 2010