| This paper presents a fast orthogo-nalization process to train a Radial Basis Function (RBF) neural network. The traditional methods for connguring the RBF weights is to use some matrix inversion or iterative process. These traditional approaches are either time consuming or computationally expensive, and often do not converge to a solution. The goal of this paper is rst to use a fast orthogo...

Cubature formulas (CFs) based on radial basis functions (RBFs) have become an important tool for multivariate numerical integration of scattered data. Although numerous works been published such RBF-CFs, their stability theory can still be considered as underdeveloped. Here, we strive to pave the way towards a more mature RBF-CFs. In particular, prove RBF-CFs compactly supported RBFs under cert...

The traditional RBF neural network has the problem of slow training speed and low efficiency, this paper puts forward the algorithm of improvement of RBF neural network by AdaBoost algorithm combined with PSO, to expand the application range of the RBF neural network. Firstly, it preprocesses the sample data in training set, and initialize the weights of test data; Secondly, it optimizes and ch...

To assess the reliability of electron beam computed tomography (EBCT), measurements of single-kidney renal blood flow (RBF), glomerular filtration rate (GFR), and intratubular contrast medium concentration (ITC) of radiographic contrast media were quantified in anesthetized pigs before and after acetylcholine-induced vasodilation and diuresis. EBCT measurements were compared with those obtained...

The efficiency of pattern recognition (PR) systems using RBF neural networks to implement their recognition function, depends a lot by the training algorithms of these neural networks and especially, by the specific techniques (e.g., supervised, clustering techniques etc.) used for RBF center positioning. Having as starting point the basic property of genetic algorithms (GA) to represent global...

Speaker identification is the process of determining which registered speaker provides a given utterance. Speaker identification required to make a claim on the identity of speaker from the Ns trained speaker in its user database. In this study, we propose the combination of clustering algorithm and the classification technique – subtractive and Radial Basis Function (RBF). The proposed techniq...

A linear autoregressive/moving-average model was developed to describe the dynamic relationship between mean arterial pressure (MAP), renal sympathetic nerve activity (SNA) and renal blood flow (RBF) in conscious rabbits. The RBF and SNA to the same kidney were measured under resting conditions in a group of eight rabbits. Spectral analysis of the data sampled at 0.4 Hz showed that the low-pass...

When the renal nerves are stimulated with sinusoidal stimuli over the frequency range 0.04-0.8 Hz, low (< or =0.4 Hz)- but not high (> or =0.4 Hz)-frequency oscillations appear in renal blood flow (RBF) and are proposed to increase responsiveness of the renal vasculature to stimuli. This hypothesis was tested in anesthetized rats in which RBF responses to intrarenal injection of norepinephrine ...

In this paper, different methods for training radial basis function (RBF) networks for regression problems are described and illustrated. Then, using data from the DELVE archive, they are empirically compared with each other and with some other well known methods for machine learning. Each of the RBF methods performs well on at least one DELVE task, but none are as consistent as the best of the...

Conventional biological treatment process is not very efficient for the treatment of petroleum refinery wastewater (PRW) that contains high-concentration of organic contaminants. Prior to biological treatment, an additional pretreatment process for PRW is required for the effluent to meet the discharge standards. While re-circulated bio-filter (RBF) has been applied as a pretreatment process in...