| 基于互相关函数的神经网络解耦器在线学习算法 |
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| 引用本文： | 李新利,白焰. 基于互相关函数的神经网络解耦器在线学习算法[J]. 华北电力大学学报(自然科学版), 2002, 29(2): 63-67 |
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| 作者姓名： | 李新利 白焰 |
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| 作者单位： | 华北电力大学自动化系,北京,102206 |
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| 基金项目： | 国家教育部高等学校骨干教师资助项目 |
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| 摘 要： | 在分散解耦的系统框架上，提出了基于ＭＩＭＯ过程互相关函数的神经网络解耦器在线学习算法。该算法定义了一组ＭＩＭＯ过程的互相关函数作为神经网络解耦器的指标函数，采用了混合遗传算法在线训练神经网络。结合实际工业对象的仿真结果，表明了该算法的有效性。
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| 关 键 词： | 神经网络 解耦 在线学习 遗传算法 |
| 文章编号： | 1007-2691(2002)02-0063-05 |
| 修稿时间： | 2001-06-27 |
Online learning algorithm of neural network decoupler based on cross correlation function |
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| LI Xin-li,BAI Yan. Online learning algorithm of neural network decoupler based on cross correlation function[J]. Journal of North China Electric Power University, 2002, 29(2): 63-67 |
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| Authors: | LI Xin-li BAI Yan |
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| Abstract: | Online learning algorithm of Neural Network Decoupler, which based on MIMO cross-correlation function, is proposed on the frame of distributed decoupling system. The algorithm defines a set of cross-correlation function of the MIMO acted as the target function of neural decoupler. The mixing genetic algorithm is adopted to train neural decoupler online. The algorithm has been evaluated through numerical simulations of an industrial object. |
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| Keywords: | neural networks decoupling online learning genetic algorithm |
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