一种快速全局优化的神经网络及其在数据融合中的应用
A FAST GLOBAL OPTIMIZATION NEURAL NETWORK AND ITS APPLICATION TO DATA FUSION
-
摘要: 本文将遗传算法的全局性和EM算法的快速性相结合,提出了一种快速全局优化神经网络,并将其应用于数据融合中。理论与实验结果表明该算法在数据融合中具有很强的鲁棒性。
-
关键词:
- 数据融合; 相关; 优化
Abstract: This paper presents a fast global optimization neural network and applies it to the data fusion. This neural network is based on the global property of genetic algorithm and the high speed property of expectation maximization (EM) algorithm. The simulation results show that this neural network is robust in the data fusion. -
Moon T K. The expectation maximization algorithm[J].IEEE Signal Processing Magazine.1996, 13(6):47-60[2]Jamshidian M, Jennrich R. Acceleration of the EM algorithm饰using quasi-Newton methods[J].J. R. Statist. Soc. B.1997, 59(3):569-587[3]陈国良, 等. 遗传算法及其应用. 北京:人民邮电出版社,1996, 69-77.[4]Long M W. Airborne Early Warning System Concepts. Boston, London: Artech House, 1992, 293-321.[5]Sarma V V S. Multisensor data fusion and decision support for airborne target identification. IEEE Trans.on SMC., 1991, SMC-21(5): 969-978.[6]王功伯. 喷气式飞机的红外辐射特性. 红外与激光技术,1989, 2(1): 26-29.[7]杨新星. 模糊神经网络数据融合算法的研究: [硕士论文]. 西安:西安电子科技大学,1997.
计量
- 文章访问数: 2079
- HTML全文浏览量: 152
- PDF下载量: 650
- 被引次数: 0