By Topic

Recognition of communication signal modulation based on SAA-SVM

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)
Rurong Huang ; Inst. of Microelectron., Southwest Jiaotong Univ., Chengdu, China ; Quanyuan Feng

Support vector machine has a wide range of applications in the communications signal modulation recognition, its parameters directly affect the recognition results, but lack of proper selection methods. In this paper, the simulated annealing algorithm has been utilized for optimization of the parameters C and g of support vector machine classifier. Compared with genetic algorithm, which is a traditional method of performing parameter searching, the rate of recognition of the proposed method increased by 3.58% and optimization time reduced by 27.7%. The results suggest that recognition of communication signal modulation based on SAA-SVM is accurate and feasible.

Published in:

Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on  (Volume:2 )

Date of Conference:

9-11 July 2010