By Topic

Efficient algorithm for kernel discriminant analysis

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)
Liang, Z. ; Inst. of Image Process. & Pattern Recognition, Shanghai Jiaotong Univ., China ; Shi, P.

An efficient algorithm for kernel discriminant analysis is developed, which applies the maximal Fisher criterion value and the minimal statistical correlation between feature vectors. In some sense, the proposed algorithm is a generalisation of Xu's method as a nonlinear feature extraction method. Experiments on ORL face database demonstrate that the proposed algorithm is effective.

Published in:

Electronics Letters  (Volume:40 ,  Issue: 25 )