Title :
Application of function link net to recognition of radar targets
Author :
Deshuang, Huang ; Erke, Mao ; Yueqiu, Han
Author_Institution :
Inst. of Autom., Beijing Inst. of Technol., China
Abstract :
This paper studies the mechanism for classification of feedforward neural networks from the geometric viewpoints. It is pointed out that the multilayer perceptron networks (MLPNs) realize hyperplane divisions in the pattern space, and the FLN realize hypercurved divisions. We give a form of generalized function link nets (GFLN), and discuss the application of a special GFLN to recognition of radar targets, and give several experimental results
Keywords :
feedforward neural nets; multilayer perceptrons; pattern classification; radar computing; radar target recognition; classification; experimental results; feedforward neural networks; generalized function link nets; hypercurved divisions; hyperplane divisions; multilayer perceptron networks; pattern space; radar targets recognition; Automation; Feedforward neural networks; Laboratories; Logic; Neural networks; Nonhomogeneous media; Pattern recognition; Radar applications; Target recognition; Transfer functions;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-2431-5
DOI :
10.1109/ICASSP.1995.479737
