[1]樊亚军,曲仕茹..利用BP神经网络实现三维飞机目标识别[J].郑州大学学报(工学版),2004,25(04):56-59.[doi:10.3969/j.issn.1671-6833.2004.04.015]
　Fan Yajun,Qu Shiru.BP neural network is used to realize three-dimensional aircraft target recognition[J].Journal of Zhengzhou University (Engineering Science),2004,25(04):56-59.[doi:10.3969/j.issn.1671-6833.2004.04.015]
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利用BP神经网络实现三维飞机目标识别()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
25卷
期数:
2004年04期
页码:
56-59
栏目:
出版日期:
1900-01-01

文章信息/Info

Title:

BP neural network is used to realize three-dimensional aircraft target recognition
作者:
樊亚军; 曲仕茹.
西北工业大学机电工程及自动化学院,陕西,西安,710072, 西北工业大学机电工程及自动化学院,陕西,西安,710072
Author(s):
Fan Yajun; Qu Shiru
关键词:
神经网络;  模式识别;  BP算法;  矩不变量
Keywords:
DOI:
10.3969/j.issn.1671-6833.2004.04.015
文献标志码:
A
摘要:
提出了一种新的飞机识别系统,采用矩的不变量的方法描述飞机的特征;采用Levenberg-Marquardt算法及弹性算法对标准的BP网络算法进行改进,从而使此系统具有识别过程迅速、稳定的特点.分别对民航机和战斗机的360张100×100不同姿态的图片进行系统识别,结果表明,该系统识别准确率在99%以上,并且识别速度较快.
Abstract:
A new aircraft identification system is proposed, which adopts the method of moment invariant to describe the characteristics of aircraft. The Levenberg-Marquardt algorithm and elastic algorithm are used to improve the standard BP network algorithm, so that the system has the characteristics of rapid and stable recognition process. The ×results show that the recognition accuracy of the system is above 360% and the recognition speed is relatively fast.

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更新日期/Last Update: 1900-01-01