References

The orthogonal kernels and its fractional form are based on the follwoing papers:

• Hadian Rasanan, A. H., Rahmati, D., Gorgin, S., & Parand, K.: A single layer fractional orthogonal neural network for solving various types of Lane–Emden equation. New Astron. 75, 101307 (2020).

• Ozer, S., Chen, C. H., & Cirpan, H. A.: A set of new Chebyshev kernel functions for support vector machine pattern classification. Pattern Recognit 44, 1435–1447 (2011).

• Dunkl, C. F., & Yuan X.: Orthogonal polynomials of several variables. Cambridge University Press 155, (2014)

• Pan, Z. B., Chen, H., & You, X. H.: Support vector machine with orthogonal Legendre kernel.International Conference on Wavelet Analysis and Pattern Recognition. IEEE, 125–130 (2012).

• Padierna, L. C, et al.: A novel formulation of orthogonal polynomial kernel functions for SVM classifiers: the Gegenbauer family. Pattern Recognition 84, 211–225 (2018).

A comprehensive guide on Fractional Orthogonal Kernels for SVM classification is available in the following book, which is set to be available online soon on February 2023:

• Jamal Amani Rad, Kourosh Parand, Snehashish Chakraverty: Learning with Fractional Orthogonal Kernel Classifiers in Support Vector Machines ,Theory, Algorithms and Applications