Title :
Radar target classification based on radial basis function and modified radial basis function networks
Author :
Guosui, Liu ; Yunhong, Wang ; Chunling, Yang ; Dequan, Zhou
Author_Institution :
Dept. of Electron. Eng., Nanjing Univ. of Sci. & Technol., China
Abstract :
This paper discusses the radial basis function (RBF) neural networks used in the radar target classification. To enhance the classification rate, the structure of the modified radial basis function (MRBF) neural network is proposed. Two kinds of MRBF networks which are called the MRBF1 network and the MRBF2 network are discussed in this paper. From the theory as well as computer simulations, we find that the performance of the MRBF network is superior to the RBF network and the MRBF2 network gets higher classification rate than the MRBF1 network
Keywords :
ART neural nets; feedforward neural nets; pattern classification; radar computing; radar target recognition; MRBF networks; MRBF1 network; MRBF2 network; RBF neural networks; adaptive resonance theory; classification rate; computer simulation; modified radial basis function networks; radar target classification; radial basis function networks; Computational modeling; Gaussian processes; Least squares approximation; Niobium; Partial response channels; Radar; Radial basis function networks;
Conference_Titel :
Radar, 1996. Proceedings., CIE International Conference of
Conference_Location :
Beijing
Print_ISBN :
0-7803-2914-7
DOI :
10.1109/ICR.1996.573808
