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	An identifying function approach for determining parameter structure of statistical learning machines 期刊论文 OAI收割 NEUROCOMPUTING, 2015, 卷号: 162, 页码: 209-217 作者: Ran, Zhi-Yong; Hu, Bao-Gang 收藏 \| 浏览/下载：29/0 \| 提交时间：2015/09/17 Identifying function Structural identifiability Statistical learning machine Kullback-Leibler divergence Parameter redundancy Reparameterization
	知识与数据驱动机器学习模型的参数可辨识性理论研究学位论文 OAI收割工学博士, 中国科学院自动化研究所: 中国科学院大学, 2014 作者: 冉智勇收藏 \| 浏览/下载：228/0 \| 提交时间：2015/09/02 可辨识性参数冗余信息论 Kullback_Leibler 散度最优化理论辨识函数 identifiability parameter redundancy information theory Kullback-Leibler divergence optimization theory identifying function
	Research on the identification for a nonlinear system (EI CONFERENCE) 会议论文 OAI收割 International Conference on Optical, Electronic Materials and Applications 2011, OEMA 2011, March 4, 2011 - March 6, 2011, Chongqing, China 作者: Liu J.; Jia P.; Liu J.; Liu J. 收藏 \| 浏览/下载：32/0 \| 提交时间：2013/03/25 The characteristic of the drift error of inertial platform is a high-order nonlinear dynamic system using the neural networks' abilities of universal approximation of differentiable trajectory and capturing system dynamic information this paper presents the drift error identifying project of inertial platform based on Elman networks structure. First the drift error model of inertial platform is established after selecting the input and output for network momentum and alterable speed algorithm is used to speed up the network convergence. On the basis of the algorithm the extended nonlinear node function in the hidden network does not only improve the learning speed of network but also satisfies the need of accuracy on system identification. Through the drift error data measured on inertial platform the training result shows that the scheme achieves satisfied identification results. (2011) Trans Tech Publications.