Title :
The MPSK signals modulation classification based on Kernel methods
Author :
Zhou, Xin ; Wu, Ying ; Wang, Bin
Author_Institution :
Zhengzhou Inf. Sci. & Technol. Inst., Zhengzhou
Abstract :
In this paper, a new classification method based on Kernel Fisher Discriminant Analysis(KFDA) is brought forward in the MPSK signals modulation classification. The fourth order cumulants of the received signals are used as the classification vector firstly, then the kernel thought is used to map the feature vector impliedly to the high dimensional feature space and linear fisher discriminant analysis is applied to signal classification. The two classifiers based on kernel function - Support Vector Machine and Kernel Fisher Discriminant Analysis are introduced in detail. In order to build effective and robust SVM and KFDA classifiers and compared with each other, the radial basis kernel function is selected, one against one or one against rest of multi-class classifier is designed, and method of parameter selection using cross-validating grid is adopted. Through the experiments it can be concluded that compared with SVM classifier, KFDA can get almost the same classification accuracy and requires less time.
Keywords :
phase shift keying; signal classification; support vector machines; MPSK signals modulation classification; classification vector; kernel fisher discriminant analysis; multiclass classifier; radial basis kernel function; support vector machine; Algorithm design and analysis; Application software; Computational complexity; Frequency synchronization; Kernel; Neural networks; Pattern classification; Signal analysis; Support vector machine classification; Support vector machines;
Conference_Titel :
Antennas, Propagation and EM Theory, 2008. ISAPE 2008. 8th International Symposium on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-2192-3
Electronic_ISBN :
978-1-4244-2193-0
DOI :
10.1109/ISAPE.2008.4735495