Open AccessA Comprehensive Estimation Method for Kernel Function of Radar Signal Classifier
Author(s) -
Xu Jing,
He Minghao,
Han Jun,
Chen Changxiao
Publication year - 2015
Publication title -
chinese journal of electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.267
H-Index - 25
eISSN - 2075-5597
pISSN - 1022-4653
DOI - 10.1049/cje.2015.01.036
Subject(s) - radial basis function kernel , variable kernel density estimation , kernel (algebra) , kernel embedding of distributions , polynomial kernel , kernel method , computer science , artificial intelligence , pattern recognition (psychology) , support vector machine , radar , kernel principal component analysis , algorithm , machine learning , mathematics , telecommunications , combinatorics
The current electromagnetism environment is fast changing and levity, the methods for evaluation Suppont vector machine (SVM) kernel functions which are used in radar signal recognition can not suit it. So kernel space separate, stability and parameter numbers were proposed in this paper to review the performance of kernel function, and a novel method for estimating kernel function was designed. By simulation, this novel method can estimate the performance of kernel function roundly, and can choose the best kernel function in different application demand for recognition.