Support Vector Machine and its Applications in Pattern Recognition
支持向量机及其在模式识别中的应用

Statistical learning theory(SLT) and support vector machine(SVM) are effective to solve problems of machine learning under the condition of finite samples. It is known that the performance of support vector machine is often better than that of some neural networks in pattern recognition,especially in high dimensional space,and they are well used in many domains for recognition. This paper at first introduces the basic theory of SLT and SVM,then points out the key problems of SVM and its research situation in recent years,and at last describes some applications of SVM in the field of pattern recognition.