提出一种用最小二乘支持向量机(LS - SVM)构造函数链接型神经网络(FLANN)逆系统的传感器动态补偿新方法。

A dynamic compensating method for transducers is presented based on functional link artificial neural networks (FLANN) inverse system constructed by least squares-support vector machine (LS-SVM).

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并且采用了最小二乘支持向量机，用等式约束取代了支持向量机中的不等式约束，降低了运算量，提高了学习效率。

The LS-SVM classifier is adopted, which replaces inequality constraints in SVM by equality constraints. So the computation consumption is reduced and the learning performance is improved.

youdao

并且采用了最小二乘支持向量机，用等式约束取代了支持向量机中的不等式约束，降低了运算量，提高了学习效率。

The LS-SVM classifier is adopted, which replaces inequality constraints in SVM by equality constraints. So the computation consumption is reduced and the learning performance is improved.

youdao