| 一种回归神经网络的快速在线学习算法 |
| |
| 引用本文： | 韦巍.一种回归神经网络的快速在线学习算法[J].自动化学报,1998,24(5):616-621. |
| |
| 作者姓名： | 韦巍 |
| |
| 作者单位： | 1.浙江大学电机系,杭州 |
| |
| 基金项目： | 国家教委留学回国人员科研启动基金 |
| |
| 摘 要： | 针对回归神经网络BP学习算法收敛慢的缺陷,提出了一种新的快速在线递推学
习算法.本算法在目标函数中引入了遗忘因子,并借助于非线性系统的最大似然估计原理成
功地解决了动态非线性系统回归神经网络模型权系数学习的实时性和快速性问题.仿真结果
表明,该算法比传统的回归BP学习算法具有更快的收敛速度.
|
| 关 键 词： | 回归神经网络 在线学习 快速算法 |
| 收稿时间： | 1996-8-12 |
A New on-Line Recursive Learning Algorithm for Recurrent Neural Network |
| |
| WEI WEI.A New on-Line Recursive Learning Algorithm for Recurrent Neural Network[J].Acta Automatica Sinica,1998,24(5):616-621. |
| |
| Authors: | WEI WEI |
| |
| Affiliation: | 1.Department of Electrical Engineering,Zhejiang University,Hangzhou |
| |
| Abstract: | In this paper a new on-line recursive learning algorithm for recurrent neural network
is proposed. It overcomes the disadvantage of the slow convergence of the recurrent BP
algorithm. The real-time learning ability and the fast convergence of the recurrent network
model of nonlinear dynamical system have been obtained by introducing the forgetting factor
in the objective function and the maximum likelihood estimation principle. Simulation results
show that the proposed algorithm performs better than the traditional recurrent BP algorithm. |
| |
| Keywords: | Recurrent neural network on-line learning fast algorithm |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
| 点击此处可从《自动化学报》浏览原始摘要信息 |
|
点击此处可从《自动化学报》下载全文 |
