A set of new kernel function for support vector machines: An approach based on Chebyshev polynomials

In this paper, we introduce a set of new kernel functions Which is derived by combining generalized Chebyshev polynomials with other standard kernel functions. New kernel functions have significant advantages over classic support Vector Machine´s (SVM) kernel functions and Chebyshev kernel. Simulation results illustrate the fact that the new set of kernel functions (in particular Chebyshev-Gaussian kernel) has noticeable improvement in decreasing error rate and support vector numbers.