基于神经网络的函数逼近问题

Function Approximation Based on Neural Network

给出了函数逼近问题 ,提出了一种新的神经网络模型 ,结合函数逼近问题及该神经网络模型给出了一种学习算法 ,并利用该算法对函数逼近进行了仿真 .

Function aproximate is introduced and a neural network model is presented.A learning algorithm is proposed which combines function approximate and neural network model.The function approximate is given as an example to show that the methold can be used practically.