Search results for "Radial Basis Function"

Exponential convergence andH-c multiquadric collocation method for partial differential equations

2003

The radial basis function (RBF) collocation method uses global shape functions to interpolate and collocatethe approximate solution of PDEs. It is a truly meshless method as compared to some of the so-calledmeshless or element-free finite element methods. For the multiquadric and Gaussian RBFs, there are twoways to make the solution converge—either by refining the mesh size

Classification and retrieval on macroinvertebrate image databases

2011

Aquatic ecosystems are continuously threatened by a growing number of human induced changes. Macroinvertebrate biomonitoring is particularly efficient in pinpointing the cause-effect structure between slow and subtle changes and their detrimental consequences in aquatic ecosystems. The greatest obstacle to implementing efficient biomonitoring is currently the cost-intensive human expert taxonomic identification of samples. While there is evidence that automated recognition techniques can match human taxa identification accuracy at greatly reduced costs, so far the development of automated identification techniques for aquatic organisms has been minimal. In this paper, we focus on advancing …

Cluster kernels for semisupervised classification of VHR urban images

2009

In this paper, we present and apply a semisupervised support vector machine based on cluster kernels for the problem of very high resolution image classification. In the proposed setting, a base kernel working with labeled samples only is deformed by a likelihood kernel encoding similarities between unlabeled examples. The resulting kernel is used to train a standard support vector machine (SVM) classifier. Experiments carried out on very high resolution (VHR) multispectral and hyperspectral images using very few labeled examples show the relevancy of the method in the context of urban image classification. Its simplicity and the small number of parameters involved make it versatile and wor…

Application of learning pallets for real-time scheduling by the use of radial basis function network

2013

The expansion of the scope and scale of products in the current business environments causes a continuous increase in complexity of logistics activities. In order to deal with this challenge in planning and control of logistics activities, several solutions have been introduced. One of the most latest one is the application of autonomy. The paradigm of autonomy in inbound logistics, can be reflected in decisions for real-time scheduling and control of material flows. Integration of autonomous control with material carrier objects can realize the expected advantages of this alternative into shop-floors. Since pallets (bins, fixtures, etc.) are some common used carrier objects in logistics, t…

A NEURAL NETWORK PRIMER

1994

Neural networks are composed of basic units somewhat analogous to neurons. These units are linked to each other by connections whose strength is modifiable as a result of a learning process or algorithm. Each of these units integrates independently (in paral lel) the information provided by its synapses in order to evaluate its state of activation. The unit response is then a linear or nonlinear function of its activation. Linear algebra concepts are used, in general, to analyze linear units, with eigenvectors and eigenvalues being the core concepts involved. This analysis makes clear the strong similarity between linear neural networks and the general linear model developed by statisticia…

Un solutore pseudospettrale basato su RBF per l'equazione di Helmoltz

2012

On a topology optimization problem governed by two-dimensional Helmholtz equation

2015

The paper deals with a class of shape/topology optimization problems governed by the Helmholtz equation in 2D. To guarantee the existence of minimizers, the relaxation is necessary. Two numerical methods for solving such problems are proposed and theoretically justified: a direct discretization of the relaxed formulation and a level set parametrization of shapes by means of radial basis functions. Numerical experiments are given. peerReviewed

Radial Basis Functions for Electronic Devices Behavioral Modeling

2006

In this paper a black-box identification technique based on the radial basis functions is used in developing global dynamic behavioural models of electronic devices from measured transient responses. This approach allows to reproduce a non-linear dynamic model of the device under modelling automatically taking into account all the physical effects relating input and output data, from measured waveform only: no knowledge of the internal structure is needed. Original application related to a bipolar junction transistor is reported and validated by comparing simulation results with measured data.

A mesh less approch based upon Radial basis function Hermite collocation method for predicting the cooling and the freezing times of foods

2005

This work presents a meshless numerical scheme for the solution of time dependent non linear heat transfer problems in terms of a radial basis function Hermite collocation approach. The proposed scheme is applied to foodstuff's samples during freezing process; evaluation of the time evolution of the temperature profile along the sample, as well as at the core, is carried out. The moving phase-change zone is identified in the domain and plotted at several timesteps. The robustness of the proposed scheme is tested by a comparison of the obtained numerical results with those found using a Finite Volume Method and with experimental results.

Referenceless thermometry using radial basis function interpolation

2014

The Proton Resonance Frequency (PRF) shift provide a method for temperature change measurements during thermotherapy. Conventional PRF thermometry works subtracting one or multiple baseline images. The method leads to artifacts caused by tissue motion and frequency drift. Various works estimating the background phase from each acquired image phase are present in literature. These algorithms are called “referenceless” because they don’t require any subtraction of baseline images for calculating temperature increment. Conventional referenceless methods estimate baseline image by fitting the background phase outside the heated region through a polynomial approach. In this work a background pha…