A novel hybrid kernel function relevance vector machine for multi-task motor imagery EEG classification

Relevance vector machine (RVM) is a sparse Bayesian probability model commonly utilized in classification problems. Kernel functions are critical for the classification capacity of RVM. The kernel functions of RVM are not limited by the Mercer theorem, which differs RVM from the traditional support vector machine (SVM). As a typical local kernel function, the Gaussian kernel function has strong interpolating capacity, while the polynomial kernel...