Title :
An improved SVDU-IKPCA algorithm for Specific Emitter Identification
Author :
Dan Xu ; Bo Yang ; Wenli Jiang ; Yiyu Zhou
Author_Institution :
Sch. of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha
Abstract :
A forecast learning method of kernel principal component analysis (KPCA) is presented for specific emitter identification (SEI) application. By constructing a symmetrical decomposition of the kernel matrix, we derived a new algorithm of incremental KPCA. Based on it, the forecast capability is developed by creating dummy samples whose kernel vectors are an extrapolation of the kernel matrix. The advance of the algorithm is verified in the SEI numerical experiment.
Keywords :
extrapolation; forecasting theory; matrix algebra; principal component analysis; radar theory; SVDU-incremental kernel principal component analysis algorithm; extrapolation methods; forecast learning method; kernel matrix; kernel vectors; specific emitter identification; symmetrical decomposition; Amplitude modulation; Automation; Data engineering; Data mining; Frequency; Kernel; Pulse amplifiers; Pulse modulation; Radar; Technology forecasting; Dynamic Pattern Recognition; Emitter Identification; KPCA; SVDU-KPCA; Specific Emitter Identification;
Conference_Titel :
Information and Automation, 2008. ICIA 2008. International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-2183-1
Electronic_ISBN :
978-1-4244-2184-8
DOI :
10.1109/ICINFA.2008.4608087
