Target recognition based on a dynamic SVM

A dynamic support vector machine method is applied to the target recognition using noise power spectrum. It searches the optimal separating hyperplane of the local space taking the target feature as center. To show better importance of each sample to the target feature, the penalty function is measured by using the distance between the target feature and each training sample.