Clifford Algebra of the Vector Space of Conics for decision boundary Hyperplanes in m-Euclidean Space

dc.creatorNieto, Isidro B.
dc.creatorVallejo, J. Refugio
dc.date2007-07-26
dc.date.accessioned2026-07-07T08:20:31Z
dc.date.available2026-07-07T08:20:31Z
dc.descriptionIn this paper we embed $m$-dimensional Euclidean space in the geometric algebra $Cl_m $ to extend the operators of incidence in ${R^m}$ to operators of incidence in the geometric algebra to generalize the notion of separator to a decision boundary hyperconic in the Clifford algebra of hyperconic sections denoted as ${Cl}({Co}_{2})$. This allows us to extend the concept of a linear perceptron or the spherical perceptron in conformal geometry and introduce the more general conic perceptron, namely the {elliptical perceptron}. Using Clifford duality a vector orthogonal to the decision boundary hyperplane is determined. Experimental results are shown in 2-dimensional Euclidean space where we separate data that are naturally separated by some typical plane conic separators by this procedure. This procedure is more general in the sense that it is independent of the dimension of the input data and hence we can speak of the hyperconic elliptic perceptron.
dc.description12 pages, 2 figures, 1 table
dc.identifierhttps://arxiv.org/abs/0707.3979
dc.identifierhttp://arxiv.org/abs/0707.3979
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/135094
dc.subjectNeural and Evolutionary Computing
dc.subjectComputational Geometry
dc.subjectI.5.1; I.5.2; I.2.6; I.3.5
dc.titleClifford Algebra of the Vector Space of Conics for decision boundary Hyperplanes in m-Euclidean Space
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