B-splines are attractive for nonparametric modelling, but choosing the optimal number and
positions of knots is a complex task. Equidistant knots can be used, but their small and …

The fitting of a curve or surface through a set of observational data is a very frequent
problem in different disciplines (mathematics, engineering, medicine,...) with many …

As the field of computer graphics develops, techniques for modeling complex curves and
surfaces are increasingly important. A major technique is the use of parametric splines in …

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A highly accessible and unified approach to the design and analysis of intelligent control
systems Adaptive Approximation Based Control is a tool every control designer should have …

The paper presents a simple technique to assign parameter values to randomly measured
points for the least squares fitting of B-spline surfaces. The parameterization is realized by …

An algebraic approach for representing multidimensional nonlinear functions by feedforward
neural networks is presented. In this paper, the approach is implemented for the …

Abstract Fuzzy model identification is an effective tool for the approx-imation of uncertain
nonlinear systems on the basis of measured data. The identification of a fuzzy model using …

Now thoroughly revised and up-dated, this book describes techniques for handling and
analysing data obtained from high-energy and nuclear physics experiments. The …

The cerebellar model articulation controller (CMAC) neural network is capable of learning
nonlinear functions extremely quickly due to the local nature of its weight updating. The …