4 papers
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning
Álvaro Sánchez-Paniagua Ríos, Juan P. Llerena, Alberto Lastra +2
The performance of Support Vector Machines (SVMs) critically depends on the kernel function choice, which enables implicit mapping of data into high-dimensional feature spaces. Whi…
Dunkl derivative from moment differentiation
Edmundo J. Huertas, Alberto Lastra, Judit Minguez Ceniceros
The work analyzes the theory of Dunkl operator as a moment differential operator. This last operator generalizes the first one whenever the sequence of moments satisfies appropriat…
Symmetric Truncated Freud polynomials
Edmundo J. Huertas, Alberto Lastra, Francisco Marcellán +1
We define the family of symmetric truncated Freud polynomials , orthogonal with respect to the linear functional defined by \begin{equation*} \langle \mathbf…
On zero behavior of higher-order Sobolev-type discrete q-Hermite I orthogonal polynomials
Edmundo J. Huertas, Alberto Lastra, Anier Soria-Lorente +1
In this work, we investigate the sequence of monic q-Hermite I-Sobolev type orthogonal polynomials of higher-order, denoted as , which are orthog…