| 基于拟牛顿法的前向神经元网络学习算法 |
| |
| 引用本文： | 杨秋贵,张杰.基于拟牛顿法的前向神经元网络学习算法[J].控制与决策,1997,12(4):357-360. |
| |
| 作者姓名： | 杨秋贵 张杰 |
| |
| 作者单位： | 华东理工大学自控系!上海200237 |
| |
| 摘 要： | 针对前向神经网络现有BP学习算法的不足,结合非线性最优化方法,提出一种基于拟牛顿法的神经元网络学习算法。该算法有效地改进了神经元网络的学习收敛速度,取得了比常规BP算法更好的收敛性能和学习速度。
|
| 关 键 词： | 神经网络 拟牛顿法 反向传播算法 |
Learning Algorithm for Neural Networks Based on Quasi-Newton Method |
| |
| Yang Qiugui,Zhang Jie,Zhang Suzhen.Learning Algorithm for Neural Networks Based on Quasi-Newton Method[J].Control and Decision,1997,12(4):357-360. |
| |
| Authors: | Yang Qiugui Zhang Jie Zhang Suzhen |
| |
| Abstract: | Since the convergence speed of the BP learning algorithm is slow, the data stability appears to be very poor. A new algorithm based on quasi -Newton method is proposed. The new algorithm, compared to the BP algorithm, has the fast learning rate and good convergence properties. |
| |
| Keywords: | neural networks quasi -Newton method back -propagation algorithm |
| 本文献已被 维普 等数据库收录！ |
|
