SAR image recognition using synergetic neural networks based on Immune Clonal Programming

被引：0
|
作者：
Gou, SP [1 ]
Jiao, LC
机构：
[1] Xidian Univ, Natl Key Lab Radar Signal Proc, Xian 710071, Peoples R China
[2] Xidian Univ, Inst Intelligent Informat Proc, Xian 710071, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2004, PT 1 | 2004年 / 3173卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A method for SAR image recognition algorithm is proposed, which makes use of the global optimal search ability and the quick local search ability of Immune Clonal Programming (ICP) [1] to obtain the prototype vectors in Synergetic Neural Networks (SNN) [2]. As a result, the recognition performance of SNN is improved. Moreover, a study has been made of multi-class recognition using SNN, a bottleneck problem of SNN, and the strategy of One-Against-One [3] is introduced in this paper. Simulation result shows the recognition accuracy rate of SNN is satisfied.
引用
收藏
页码：918 / 923
页数：6
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