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贝叶斯算法在导引系统中的应用与研究

Application and Research of Guidance System Based on Bayesian Algorithm
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摘要 为提升导引系统的路径搜索效率,研究贝叶斯算法在导引功能中的推理过程,采用嵌入式方案,基于REAL210开发板和STM32F407处理器对导引系统的硬件进行了设计,并针对系统的初始化、中断等控制流程进行了软件设计。导引系统采用超声波测距方式,通过四阶带通滤波电路提升了抗干扰能力。 In order to improve the path search effi ciency of guidance system, the Bayesian network learning and reasoning process is analyzed. With the embedded scheme, the hardware is designed based on REAL210 plate and STM32F407 processor, and the software is designed according to the process of system initialization, interrupt control. Ultrasonic ranging method is used in the system, and the antiinterference ability is improved through the fourthorder bandpass fi lter circuit.
作者 刘华伟 戚振
出处 《中国仪器仪表》 2016年第11期57-60,共4页 China Instrumentation
关键词 贝叶斯算法 路径搜索 导引系统 嵌入式系统 滤波U Bayesian algorithm Path search Guidance system Embedded system Filter
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  • 1史建国,高晓光.离散动态贝叶斯网络的直接计算推理算法[J].系统工程与电子技术,2005,27(9):1626-1630. 被引量:36
  • 2高晓光,史建国.变结构离散动态贝叶斯网络及其推理算法[J].系统工程学报,2007,22(1):9-14. 被引量:22
  • 3Jensen F V. An Introduction to Bayesian Networks. New York: Springer, 1996.
  • 4Jensen F V. Bayesian Networks and Decision Graphs. New York: Springer, 2001.
  • 5Dean T, Kanazawa K. A model for reasoning about persistence and causation. Computational Intelligence, 1989, 5(3): 142-150.
  • 6Rusell S, Norving P. Artificial Intelligence: A Modern Approach (Second Edition). New Jersey: Prentice Hall, 2003. 559-580.
  • 7Suandi S A, Enokida S, Ejima T. Face pose estimation from video sequence using dynamic Bayesian network. In: Proceedings of the IEEE Workshop on Motion and Video Computing. Copper Mountain, USA: IEEE, 2008. 1-8.
  • 8Han P X, Mu R J, Cui N G. Active and dynamic multi-sensor information fusion method based on dynamic Bayesian networks. In: Proceedings of the International Conference on Mechatronics and Automation. Changchun, China: IEEE. 2009. 3076-3080.
  • 9Peter Hearty, Norman Fenton, David Marquez, Martin Neil. Predicting project velocity in XP using a learning dynamic Bayesian network model. IEEE Transactions on Software Engineering, 2009, 35(1): 124-137.
  • 10Ghahramani Z. An introduction to hidden Markov models and Bayesian networks. International Journal of Pattern Recognition and Artificial Intelligence, 2001, 15(1): 9-42.

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