单层神经网络的快速学习算法研究
Study on the Fast Learning Algorithm of Single-layer Neural Networks
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摘要: 该文提出一种适用于单层神经网络(SNN)训练的新颖的广义误差函数,给出了 SNN新的快速学习算法(FLA).进一步提出了一种广义系统辨识模型,对FLA的收敛性进 行了理论分析.实验表明:文中给出的新FLA比Karayiannis的LFA具有更快的收敛速度.Abstract: This paper proposes a new generalized criterion for the training of single-layer neural networks, which leads to a novel fast learning algorithm for single-layer neural network. In order to analyse the convergent properties of the fast algorithm we developed, a new generalized system identification model is also presented. Experiment results show that the fast algorithm proposed in this paper performs the training of neural nework faster than the corresponding learning algorithm given by Karayiannis.
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Key words:
- Single-layer NN /
- fast BP algorithm /
- statistical analysis
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