Hybrid robust LS-SVMR with outliers for MIMO system

In this study, a hybrid robust LS-SVMR approach is proposed to deal with training data sets with outliers dor MIMO system. The proposed approach consists of two stages of strategies. The first stage is for data preprocessing and a support vector regression is used to filter out outliers. Then, the training data set except for outliers, called as the reduced training data set, is directly used in training the non-robust least squares support vector machines for regression (LS-SVMR) for MIMO system in the second stage. Consequently, the learning mechanism of the proposed approach is much easier than the weighted LS-SVMR approach. Based on the simulation results, the performance of the proposed approach with non-robust LS-SVMR is superior to the weighted LS-SVMR approach for MIMO system when the outliers exist.