We consider a preconditioned Krylov subspace iterative algorithm presented by Faul et al. (IMA Journal of Numerical Analysis (2005) 25, 1—24) for computing the coefficients of a radial basis function interpolant over N data points. This preconditioned Krylov iteration has been demonstrated to be extremely robust to the distribution of the points and the iteration rapidly convergent. However, th...

This paper presents an axiomatic approach for constructing radial basis function (RBF) neural networks. This approach results in a broad variety of admissible RBF models, including those employing Gaussian RBF's. The form of the RBF's is determined by a generator function. New RBF models can be developed according to the proposed approach by selecting generator functions other than exponential ...

A novel particle swarm optimisation (PSO) tuned radial basis function (RBF) network model is proposed for identification of non-linear systems. At each stage of orthogonal forward regression (OFR) model construction process, PSO is adopted to tune one RBF unit’s centre vector and diagonal covariance matrix by minimising the leave-one-out (LOO) mean square error (MSE). This PSO aided OFR automat...

Dautzenberg M, Kahnert A, Stasch JP, Just A. Role of soluble guanylate cyclase in renal hemodynamics and autoregulation in the rat. Am J Physiol Renal Physiol 307: F1003–F1012, 2014. First published September 10, 2014; doi:10.1152/ajprenal.00229.2014.—We studied the influence of soluble guanylate (sGC) on renal blood flow (RBF), glomerular filtration rate (GFR), and RBF autoregulation and its r...

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...

The first appearance of G1 during Drosophila embryogenesis, at cell cycle 17, is accompanied by the down-regulation of E2F-dependent transcription. Mutant alleles of rbf were generated and analyzed to determine the role of RBF in this process. Embryos lacking both maternal and zygotic RBF products show constitutive expression of PCNA and RNR2, two E2F-regulated genes, indicating that RBF is req...

The receptor-binding factor (RBF) for the avian oviduct progesterone (Pg) receptor (PR) has previously been shown to be a unique 10-kDa nuclear matrix protein that generates high affinity PR-binding sites on avian DNA. This paper describes the use of Southwestern blot and DNA gel shift analyses with RBF protein to identify a minimal 54-base pair RBF-binding element in the matrix-associated regi...

Hierarchical RBF networks consist of multiple RBF networks assembled in different level or cascade architecture. In this paper, an evolved hierarchical RBF network was employed to detect the breast cancel. For evolving a hierarchical RBF network model, Extended Compact Genetic Programming (ECGP), a tree-structure based evolutionary algorithm and the Differential Evolution (DE) are used to find ...

Landmark-based registration using radial basis functions (RBF) is an efficient and mathematically transparent method for the registration of medical images. To ensure invertibility and diffeomorphism of the RBF-based vector field, various regularization schemes have been suggested. Here, we report a novel analytic method of RBF regularization and demonstrate its power for Gaussian RBF. Our anal...