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Proceedings Paper

Fuzzy radial basis function neural network for radar target recognition
Author(s): Yunhong Wang; Guo-Sui Liu; Guangmin Sun; Yiding Wang
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Paper Abstract

The radial basis function network (RBFN) is analyzed and the fuzzy radial basis function network (FRBFN) which is more suitable for the radar target recognition is proposed in this paper. Here both of the two networks are used as classifiers. This FRBFN utilize fuzzy clustering method to determine the structure of the net. The generalization property of the two networks are discussed. It is shown from the theoretical analysis and experiment that the FRBFN has better generalization property. The Doppler echoes of the targets gotten from a current surveillance radar are used in the experiment. The experimental results shows that the classification rate of the FRBFN is higher than that of the RBFN. The network proposed in this paper is promising in the application of radar target recognition.

Paper Details

Date Published: 4 April 1997
PDF: 8 pages
Proc. SPIE 3077, Applications and Science of Artificial Neural Networks III, (4 April 1997); doi: 10.1117/12.271529
Show Author Affiliations
Yunhong Wang, Nanjing Univ. of Science and Technology (China)
Guo-Sui Liu, Nanjing Univ. of Science and Technology (China)
Guangmin Sun, Nanjing Univ. of Science and Technology (China)
Yiding Wang, Nanjing Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 3077:
Applications and Science of Artificial Neural Networks III
Steven K. Rogers, Editor(s)

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