针对位置敏感探测器(PSD)固有的非线性，提出一种基于BP优化算法的PSD非线性校正方法。以传统的牛顿算法为基础，推导了LevenbergMarquardt算法，即BP优化算法的相关原理。采用Matlab软件编程,网络采用具有2个中间隐层的结构形式，2个隐层使用的神经元数分别为40和30,最大训练次数取500次，利用sim函数计算并仿真网络输出，网络输出误差均在0.001 mm之内，其中最大误差不超过0.003 mm，实现了对PSD非线性的校正。
Abstract
For the inherent nonlinearity of position sensitive detector (PSD),a PSD nonlinear correction method based on backpropagation (BP) optimization algorithm was proposed.Based on the traditional Newton algorithm , the relevant principle of LevenbergMarquardt algorithm was deduced, that is the BP optimization algorithm.The Matlab software was used for programming, the network utilized the structure having 2 hidden layers,and the numbers of neurons for them were 40 and 30,respectively,the max training time was 500,and finally the results were computed by sim function and outputed through simulated network.Through verified by experiment, the network output error is almost within 0.001 mm, of which the maximum error is less than 0.003 mm, achieving the PSD nonlinear correction.
关键词
神经网络 /
BP优化算法 /
PSD非线性
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Key words
neural networks /
BP optimization algorithm /
PSD nonlinear
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