A new support vector neural network inference system

Authors:
Ling Wang;Zhi-Chun Mu
Affiliations:
Information Engineering School, University of Science and Technology, Beijing, China;Information Engineering School, University of Science and Technology, Beijing, China
Venue:
Intelligent information processing II
Year:
2004

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The nature of statistical learning theory

The nature of statistical learning theory
Support-Vector Networks

Machine Learning

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Abstract

In this paper, we present a new support vector neural network inference system (SVNNIS) for regression estimation. The structure of the proposed SVNNIS can be obtained similar to that in the support vector regression (SVR), while the output of the SVNNIS is unbiased compared with the SVR and the weights can be updated by the recursive least square method with forgetting factor. The advantage of this system is its good generalization capability. The simulation result illustrates the effectiveness of the proposed SVNNIS.