This paper proposes a neural-network-based method for the computation of the configuration space for robotic manipulators. The configuration space can be obtained by repeatedly computing configuration space patterns for elementary obstacle primitives. For any manipulator, these patterns depend only on the distance between the base of the manipulator and the obstacle primitive. An RBF-network is...

The problem is said to be tractable if there exist constants c, α, β independent of q (but possibly dependent on μ and F) such that En(F , μ) ≤ cqαn−β. We explore different regions (including manifolds), function classes, and measures for which this problem is tractable. Our results include tractability theorems for integration with respect to non-tensor product measures, and over unbounded and...

In this paper, we deal with the problem of function approximation from a given set of input/output data. This problem consists of analyzing these training examples so that we can predict the output of the model given new inputs. We present a new method for function approximation of the I/O data using radial basis functions (RBFs). This approach is based on a new efficient method of clustering o...

This paper presents numerical solution of elliptic partial differential equations Poisson’s equation using a combination of logarithmic and multiquadric radial basis function networks. This method uses a special combination between logarithmic and multiquadric radial basis functions with a parameter r. Further, the condition number which arises in the process is discussed, and a comparison is m...

With the aim of classifying sperm whales, this report compares two methods that can use Gaussian functions, a radial basis function network, and support vector machines which were trained with two different approaches known as C-SVM and ν-SVM. The methods were tested on data recordings from seven different male sperm whales, six containing single click trains and the seventh containing a comple...

The hydration of biomolecules is vitally important in molecular biology, so in this paper thesolvation energy and radial distribution function of DNA bases have been calculated by theMonte Carlo simulation.The geometries of isolated Adenine, Guanine, Cytosine, and Thyminehave been optimized using 6-31+G(d,p) basis function sets. These geometries then will be used inthe Monte Carlo calculation o...

In this paper, we present a direct solution method based on wavelet networks for image compression. Wavelet networks are a combination of radial basis function (RBF) networks and wavelet decomposition, where radial basis functions were replaced by wavelets. The results show that the wavelet networks approach succeeded to improve high performances in terms of compression ratio and reconstruction...

The existing Chinese Minorities OCR system is mainly oriented in the "literacy" level, the script recognition has not attracted the attention it deserves, and the area of recognizing the kinds of Chinese minority scripts is still in a blank. The method of recognizing the kinds of Chinese minority scripts based on wavelet analysis and Radial Basis Function Network (RBFN) is presented which adopt...

In this paper, a new approach for the compensation of unknown periodic disturbances by means of a neural network is presented. The neural controller supports the conventional controller by suppressing periodic disturbances. This is done by online learning in order to adapt to different operating conditions and to time varying unknown disturbances. The neural network learns an optimal compensati...

| Adaptive learning dynamics of the Radial Basis Function Network (RBFN) are compared with a scale-based clustering technique Won93] and a relationship between the two is pointed out. Using this link, it is shown how scale-based clustering can be done using the RBFN, with the Radial Basis Function (RBF) width as the scale parameter. The technique suggests the \right" scale at which the given da...