摘要
探讨了采用神经网络校准仪器非线性的方法,并用递推预报误差算法训练神经网络.理论分析和实验结果表明,神经网络方法优于传统的最小二乘法,能够取得很好的效果.
The method of calibrating the nonlinearity of the instrument by using nervous network is investigated. The nervous network is trained by recurrence forecast error algorithm. The theoretical analysis and the test result show that the nervous network method is better than the least square method and can get excellent effects.
出处
《自动化仪表》
CAS
北大核心
1997年第7期15-17,共3页
Process Automation Instrumentation