基于极限学习机的空间配准方法
发布时间：2018-08-09 12:40
【摘要】：对极限学习机的特点及适用条件进行了探讨,在此基础上提出和实现了一种基于极限学习机的空间配准方法,并与基于广义最小二乘和神经网络的配准方法在多种场景下进行了仿真比较,结果验证了基于极限学习机的空间配准方法的性能优势。
[Abstract]:The characteristics and applicable conditions of extreme learning machines are discussed. On this basis, a spatial registration method based on limit learning machine is proposed and implemented. The simulation is compared with the registration method based on generalized least squares and neural networks in a variety of scenes. The results prove the spatial registration method based on the limit learning machine. Performance advantages.
【作者单位】： 北方自动控制技术研究所;
【基金】：国家自然科学基金资助项目(61371064)
【分类号】：E926.4;TP181
本文编号：2174103
[Abstract]:The characteristics and applicable conditions of extreme learning machines are discussed. On this basis, a spatial registration method based on limit learning machine is proposed and implemented. The simulation is compared with the registration method based on generalized least squares and neural networks in a variety of scenes. The results prove the spatial registration method based on the limit learning machine. Performance advantages.
【作者单位】： 北方自动控制技术研究所;
【基金】：国家自然科学基金资助项目(61371064)
【分类号】：E926.4;TP181
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1 刘祯;朱元武;樊兴;武云鹏;;网络化火控系统空间配准技术仿真[J];火力与指挥控制;2014年06期
，本文编号：2174103
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