The recently proposed domain-free discretization (DFD) method is based on the Lagrange interpolation and polynomial-based differential quadrature (PDQ) method. In this article, the radial basis function (RBF) approximation is used in the DFD method as the interpolation scheme for function approximation, and the RBF-DQ method is applied to derivative approximation. The new variant of DFD method ...

This paper proposes a new face recognition approach by using the Discrete Cosine Transform (DCT) and Hierarchical Radial Basis Function Network (HRBF) classification model. The DCT is employed to extract the input features to build a face recognition system, and the HRBF is used to identify the faces. Based on the pre-defined instruction/operator sets, a HRBF model can be created and evolved. T...

We introduce a master–worker framework for parallel global optimization of computationally expensive functions using response surface models. In particular, we parallelize two radial basis function (RBF) methods for global optimization, namely, the RBF method by Gutmann [Gutmann, H.M., 2001a. A radial basis function method for global optimization. Journal of Global Optimization 19(3), 201–227] ...

this paper extends the sequential learning algorithm strategy of two different types of adaptive radial basis function-based (rbf) neural networks, i.e. growing and pruning radial basis function (gap-rbf) and minimal resource allocation network (mran) to cater for on-line identification of non-linear systems. the original sequential learning algorithm is based on the repetitive utilization of s...

‎Radial basis function method has been used to handle linear and‎ ‎nonlinear equations‎. ‎The purpose of this paper is to introduce the method of RBF to‎ ‎an existing method in solving nonlinear two-level iterative‎ ‎techniques and also the method is implemented to four numerical‎ ‎examples‎. ‎The results reveal that the technique is very effective‎ ‎and simple. Th...

In the present paper, an approach is proposed for structural topology optimization based on combination of Radial Basis Function (RBF) Level Set Method (LSM) with Isogeometric Analysis (IGA). The corresponding combined algorithm is detailed. First, in this approach, the discrete problem is formulated in Isogeometric Analysis framework. The objective function based on compliance of particular lo...

The previous work in [1], Tseng et al. have designed a fractional order differentiator using radial basis function by directly truncating the coefficients to approximate the fractional order derivative Dα of the given digital signal. This paper presents the designing of fractional order differentiator using radial basis function and window. Three design examples are given to illustrate that the...

We have developed a new algorithm, RBF-MREIT, for Magnetic Resonance Electrical Impedance Tomography (MREIT) by applying the radial basis function (RBF) network and Simplex method. RBF-MREIT uses only one component of the measured magnetic flux density to reconstruct the conductivity images, and provides a solution to the rotation problem in MREIT. The proposed algorithm is tested on a three-sp...

Difficulty was known to get satisfactory measurement effect on precision in capacitive grain’s moisture measurement due to many influencing factors, such as temperature, species, compaction and so on. The data confusion method of Radial Basis Function (RBF) nerve network is adopted. With improved orthogonal optimal method, the RBF nerve network’s weight factors can be obtained. This method can ...