Autocorrelation Kernel Functions for Support Vector Machines

Kernel functions (kernel) are key part and the hard issue of support vector machines. We research the relation of kernel functions and nonlinear mappings and mapped spaces. A new kind of admissible support vector machines kernel is presented. It is autocorrelation kernel. The theory proofs certify that autocorrelation functions are admissible support vector machines kernel. Several experiments also showed the validity of the autocorrelation kernel in classification and regression.