<abstract xmlns="http://www.w3.org/1999/xhtml"><p> The pattern analysis technology based on kernel methods is a new technology, which combines good performance and strict theory. With support vector machine, pattern analysis is easy and fast. But the existing kernel function fits the requirement. In the paper, we explore the new mixed kernel functions which are mixed with Gaussian and Wavelet function, Gaussian and Polynomial kernel function. With the new mixed kernel functions, we check different parameters. The results shows that the new mixed kernel functions have good time efficiency and accuracy. In image recognition we used SVM with two mixed kernel functions, the mixed kernel function of Gaussian and Wavelet function are suitable for more states.</p></abstract>

The pattern analysis technology based on kernel methods is a new technology, which combines good performance and strict theory. With support vector machine, pattern analysis is easy and fast. But the existing kernel function fits the requirement. In the paper, we explore the new mixed kernel functions which are mixed with Gaussian and Wavelet function, Gaussian and Polynomial kernel function. With the new mixed kernel functions, we check different parameters. The results shows that the new mixed kernel functions have good time efficiency and accuracy. In image recognition we used SVM with two mixed kernel functions, the mixed kernel function of Gaussian and Wavelet function are suitable for more states.

New Mixed Kernel Functions of SVM Used in Pattern Recognition

Harbin University of Science and Technology, China

Cybernetics and Information Technologies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"New Mixed Kernel Functions of SVM Used in Pattern Recognition"}

The pattern analysis technology based on kernel methods is a new technology, which combines good performance and strict theory. With support vector machine,...

New Mixed Kernel Functions of SVM Used in Pattern Recognition

Online veröffentlicht: 20. Okt. 2016

Seitenbereich: 5 - 14

DOI: https://doi.org/10.1515/cait-2016-0047

Schlüsselwörter
Support vector machine, kernel functions, pattern recognition, Wavelet function

© by Hao Huanrui

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

New Mixed Kernel Functions of SVM Used in Pattern Recognition

Online veröffentlicht: 20. Okt. 2016

Seitenbereich: 5 - 14

DOI: https://doi.org/10.1515/cait-2016-0047

SchlüsselwörterSupport vector machine, kernel functions, pattern recognition, Wavelet function

© by Hao Huanrui

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
Support vector machine, kernel functions, pattern recognition, Wavelet function