摘要
介绍了利用神经网络的非线性逼近能力和自学习能力,对未知表达式的曲线进行辨识,并利用从曲线的神经网络辨识模型中得到的数据,建立一个数控系统的神经网络插补控制器,实现对未知表达式曲线的插补。通过理论研究和仿真试验表明,这种方法能够较好的完成这类曲线的插补。
This paper introduces that neural networks have strong ability of nonlinear processing and selflearning.By using these ability, simulating a expression of the unknown-formular curve .Then building the neural networks model for CNC interpolation, by using the data points that get from the simulated expression.The research and the simulation calculation demonstrate this method has good ability to solve the interpolation of these unknown-formular curves.
出处
《机械》
2007年第4期4-6,12,共4页
Machinery
关键词
神经网络
插补
未知表达式曲线
neural network
interpolation
unknown-formular curve
