测试技术学报2005，Vol.19Issue(4)：453-458,6.
BP神经网络在测试系统动态补偿中的应用
Application of Back Propagation Artificial Neural Networks on Dynamic Compensation of Measurement Systems
摘要
Abstract
Nonlinear dynamic compensation of measurement systems is an important aspect in the field of instrument technique. The back propagation (BP) neural network is proposed for nonlinear dynamic compensation of measurement systems, as its architecture is determined only by the number of nodes in the input, hidden and output layers. With the nonlinear mapping behavior, the BP neural network can catch up with the dynamic response of the system. A recursive prediction error algorithm which converges fast is applied to train the BP neural network. Experimental results show that the performance of the BP neural network model conforms to the measurement system to be compensated,proving the method is not only effective but of high precision.关键词
动态补偿/神经网络/递推预报误差算法Key words
dynamic compensation/neural networks/recursive prediction error algorithm分类
信息技术与安全科学引用本文复制引用
田社平,韦红雨,王志武,颜国正..BP神经网络在测试系统动态补偿中的应用[J].测试技术学报,2005,19(4):453-458,6.基金项目
国家自然科学基金资助项目(30270382) （30270382）
