| 非线性随机动态系统学习建模方法 |
| |
| 引用本文： | 覃祖旭,张洪钺.非线性随机动态系统学习建模方法[J].北京航空航天大学学报,1996,22(6):682-686. |
| |
| 作者姓名： | 覃祖旭 张洪钺 |
| |
| 作者单位： | 北京航空航天大学自动控制系 |
| |
| 摘 要： | 在动态神经网络及扩展卡尔曼滤波算法的基础上，提出了对非线性随机动态系统进行学习建模的迭代算法，用这种方法对非线性随机系统建模，可以获得更准确伯系统模型，并可对非线性随机系统进行状态估计。最后给出相应算法及仿真结果。
|
| 关 键 词： | 神经网络 非线性系统 卡尔曼滤波 |
LEARNING METHOD FOR NONLINEAR STOCHATICS DYNAMIC SYSTEM MODELING |
| |
| Qin Zuxu,Zhang Hongyue.LEARNING METHOD FOR NONLINEAR STOCHATICS DYNAMIC SYSTEM MODELING[J].Journal of Beijing University of Aeronautics and Astronautics,1996,22(6):682-686. |
| |
| Authors: | Qin Zuxu Zhang Hongyue |
| |
| Abstract: | A modeling method for nonlinear stochastics dynamic system(NSDS) based on neural network and extended Kalman filter(EKF) is presented. Using this method, the contaminated data by noise can be filtered by EKF. A dynamic neural network(DNN) which is a good approximation to the deterministic part of the NSDS can be obtained. Meanwhile the DNN can be used as a state estimator for the NSDS. In the end of the paper a simulation is shown. |
| |
| Keywords: | neural networks non linear systems Kalman filtering |
| 本文献已被 CNKI 维普 等数据库收录！ |
