人工神经网在二维PSD器件非线性修正中的应用

介绍了一种应用人工神经网对二维PSD器件非线性进行修正的方法。对光斑在二维PSD光敏面上的横向位移，以光斑的二维坐标集合为神经网的期望输出，以PSD输出的二维坐标集合为神经网的训练样本，对神经网络进行训练。利用神经网络所具有的非线性映射能力，在训练结束后即可建立PSD输入与输出的近似线性关系。结果表明修正后的PSD器件可以实现任意输入的实时非线性修正。

Application of Artificial Neural Networks in Non-linearity Correction of Two Dimension PSD Device

By using BP artificial neural networks, a method of non-linearity correction for two dimensional PSD device is presented. When a light point moves in the detective area of PSD, the coordinates of the point at different positions are used as designed output of the networks and the output coordinates of the PSD are used as learning input of the networks, and a learning procedure is carried out. According to the ability of non-linear mapping of artificial neural networks, a linear relationship between input and output of the networks is set up after learning. Results show that learned networks can correct any non-linearity error in real time.