Multiple Kernel Sparse Representation Based Gaussian Kernel and Power Kernel

Sparse representation classification (SRC) and kernel method have been successfully used in pattern recognition. On account of the limitations of the single kernel function, we proposed multiple kernel sparse classification method in face recognition to improve human face recognition rate. The Power kernel function has a good stability, and the Gaussian kernel function has good practicability. The Power kernel function and Gaussian kernel function are linearly combined. Through the transformation of different kernel space, we effectively extract the nonlinear structure information of the human face. Many experimental results show that the multiple kernel sparse representation classification algorithms that based on Power kernel function and Gaussian kernel function have higher recognition rate than that only using the single kernel sparse representation classification.