DocumentCode :
2103024
Title :
The Application of Genetic Algorithm on the Training of Neural Network for Acoustic Target Classification
Author :
Hou, Weimin ; Bao, Ming ; Shang, Yan ; Wang, Jing
Author_Institution :
Inst. of Inf. Sci. & Eng., Hebei Univ. of Sci. & Technol., Shijiazhuang
fYear :
2008
fDate :
21-22 Dec. 2008
Firstpage :
62
Lastpage :
65
Abstract :
The paper adopted back-propagation neural network to classify acoustic target the wheeled and tracked vehicles was the researched target of this paper. Genetic Algorithm (GA) was first used to make global search of the suitable combination of the number of hidden nodes, the learning rate and momentum coefficient, the experiment in this paper will show that the neural network trained by GA has better performance in classifying wheeled and tracked target.
Keywords :
acoustic signal processing; backpropagation; genetic algorithms; neural nets; signal classification; target tracking; acoustic target classification; back-propagation neural network; genetic algorithm; learning rate; momentum coefficient; neural network training; Acoustic applications; Evolutionary computation; Genetic algorithms; Information science; Information technology; Intelligent networks; Intelligent vehicles; Neural networks; Target tracking; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Information Technology Application Workshops, 2008. IITAW '08. International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3505-0
Type :
conf
DOI :
10.1109/IITA.Workshops.2008.94
Filename :
4731881
Link To Document :
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