SVM based on subclass and application of underwater acoustic target recognition

In view of separability trait of objective class space to highly nonlinear problem, the support vector machine based on subclass integrating the dynamic clustering with the support vector machine (SVM) was researched. A method was put forward that measured the penalization-degree using the subclass center as base point. On the basis of objective class decomposed as subclasses by using dynamic clustering, the penalization degree of each sample was measured by synthetically considering the relation between each sample and its subclass, the relation between the subclass and its objective class and the relation in different objective classes. At last, the SVM based on subclass was applied in the underwater acoustic target recognition. Experiment results show that the SVM based on subclass is more robust than the traditional SVM.