Title :
A RBF neural networks based feature
Author :
Lianglong Da ; Guangzhi Shi ; Junchuan Hu ; Yuyang Li
Author_Institution :
Navy Submarine Acad., Qingdao, China
Abstract :
A RBF (Back-Propogation) neural networks based feature is applied to the target recognition, which aims at only recognition of the target feature and searches the hyperplane of the local space taking the target feature as center. The classifier integrates the target feature with RBF ANNs. It evaluates importance of each sample to the target feature by using expected output of the dynamic ANNs training process. Experiment results show that it is more robust than the traditional method.
Keywords :
backpropagation; learning (artificial intelligence); object recognition; radial basis function networks; RBF neural networks based feature; back-propagation neural networks; dynamic ANN training process; target recognition; Artificial neural networks; Biological system modeling; Helium; Marine vehicles; Support vector machines; Target recognition; Training; RBF ANNs; expected output of training sample; target recognition; the dynamic training set;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
DOI :
10.1109/WCICA.2010.5554312
