摘要
在BP神经网络现有算法的基础上提出一种新的算法,该算法的基本原理是任选一组自由权,通过解线性方程组求得隐层权,将选定的自由权与求得的权合在一起,就得到所需的学习权值。该算法不存在传统方法的局部极小及收敛速度慢的问题。
The BP neural networks algorithm presented in this paper is based on the existing algorithm, which basic principle is choosing a freedom weight, by solving the linear equations to achieve hidden layer, combination freedom weight, then obtain weight is necessary weight. This algorithm hasn't the traditional method such as the local minimum and the slower rate of convergence in BP neural networks algorithm.
出处
《电脑知识与技术（过刊）》
2009年第2X期1197-1198,共2页
Computer Knowledge and Technology
