Study on radar emitter recognition signal based on rough sets and RBF neural network

With the development of new type and use of radar emitter, it is more difficult to recognize radar emitter signal. The radar emitter signal information is converted into discrete value in this paper. The attribute of radar emitter signal is reduced and the decision rules are extracted based on rough...

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Bibliographic Details
Published in2009 International Conference on Machine Learning and Cybernetics Vol. 2; pp. 1225 - 1230
Main Authors Zheng-Chao Zhang, Xin Guan, You He
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2009
Subjects
Cybernetics
Data mining
Helium
Information systems
Machine learning
Neural networks
Programmable logic arrays
Radar emitter recognition
Radar theory
RBF neural network
Rough K-means
Rough sets
Rough Sets theory
Signal analysis
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Summary:With the development of new type and use of radar emitter, it is more difficult to recognize radar emitter signal. The radar emitter signal information is converted into discrete value in this paper. The attribute of radar emitter signal is reduced and the decision rules are extracted based on rough sets. Then the cluster center of radial basis function (RBF) neural network is gain by rough K-means cluster method. The RBF neural network is constructed with the help of decision rules extracted from information table. The simulation result shows this radar emitter recognition model base on rough sets and RBF neural network can cut down the redundant attribute, lessen the neural network structure and recognize radar emitter signal effectively.
ISBN:9781424437023
1424437024
ISSN:2160-133X
DOI:10.1109/ICMLC.2009.5212449