Fuzzy B-Spline Surface Modeling

Fuzzy B-spline Modeling of Uncertainty Data

In this paper, we purposed a new method in modeling the uncertainty data based on the theory of fuzzy sets and the interpolation B-spline model curve. The uncertainty data firstly defined by using fuzzy number concept and fuzzy relation by defined them in real data form. The existed coefficient control of interpolation B-spline basis function is substituted with the fuzzy data points(FDPs) whic...

Constructing Fuzzy Controllers with B Spline Models

We interpret a type of fuzzy controller as an inter polator of B spline hypersurfaces B spline basis func tions of di erent orders are regarded as a class of mem bership functions MFs with some special properties These properties lead to several interesting conclusions about fuzzy controllers if such membership functions are employed to specify the linguistic terms of the input variables We sho...

Functional networks for B-spline surface reconstruction

Recently, a new extension of the standard neural networks, the so-called functional networks, has been described [E. Castillo, Functional networks, Neural Process. Lett. 7 (1998) 151–159]. This approach has been successfully applied to the reconstruction of a surface from a given set of 3D data points assumed to lie on unknown Bézier [A. Iglesias, A. Gálvez, Applying functional networks to CAGD...

Periodic B - Spline Surface Skinning Of

Meshless Parameterization and B-Spline Surface Approximation

This paper proposes a method for approximating unorganized points in lR 3 with smooth B-spline surfaces. The method involves: meshless parameteri-zation; triangulation; shape-preserving reparameterization; and least squares spline approximation.