摘要
介绍了一种基于支持向量机的解决传感器系统非线性特性问题的新方法。支持向量机是Vapnik教授提出的基于统计学习理论的新一代机器学习技术,它有效地解决了小样本学习问题,因此该方法对样本数量没有特殊的要求。实验证明该方法有效,同时研究表明该方法也能用于其他系统的非线性校正。
The paper presents a new method of solving the problem of the nonlinearity rectification in a sensor system by using a support vector machine（ SVM） that is a new machine with learning algorithm based on a statistic learning theory created by prof. Vapnik. The SVM can solve small-sample learning problems with no special demand for data number. The experimental result shows that this method is effective. The research indicates that the method can be also used to realize the nonlinearity rectification in other similar systems.
出处
《工业仪表与自动化装置》
2005年第4期3-5,47,共4页
Industrial Instrumentation & Automation
基金
安徽省自然科学基金资助项目(042310)
