摘要
在应用多种方法提取目标噪声中分类特征的研究基础上,本文设计出基于模糊理论的多神经网络融合分类器,其研究重点主要包括有监督分类的模糊聚类神经网络分类、多神经网络与模糊综合分析相结合的融合分类。基于大量海试实测信号样本的多组实验表明,该分类方法具有良好的工程应用前景。
By using the classification feature information extracted from target noise ,a target classification method based on integration of multiple fuzzy clustering neural networks and fuzzy comprehensive analysis is put forward. The classification experiment results of real target signals confirm the feasibility and effectiveness of the proposed method.
出处
《船舶工程》
CSCD
北大核心
1999年第6期43-47,共5页
Ship Engineering
关键词
水下目标识别
模糊聚类
神经网络
Underwater target recognition,Fuzzy clustering neural network ,Fuzzy comprehensive analysis