By Topic

Hybrid wavelet Support Vector Regression

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

2 Author(s)
George, J. ; Med. Imaging Res. Group, Network Syst. &Technol. (P) Ltd., Trivandrum ; Rajeev, K.

Support vector regression using a hybrid wavelet support vector kernel is presented in this paper. A hybrid wavelet kernel construction for support vector machine is introduced. The construction involves a multi-dimensional sinc wavelet function together with one of the conventional kernel functions. We show that the hybrid kernel is an admissible support vector (SV) kernel. The hybrid kernels thus constructed are used for the function approximation problem. The experimental results show that the hybrid kernels provide better function approximation in the mapped feature space compared to conventional kernels.

Published in:

Cybernetic Intelligent Systems, 2008. CIS 2008. 7th IEEE International Conference on

Date of Conference:

9-10 Sept. 2008