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Basis Function

Writer Identification and Recognition Using Radial Basis Function

Writer Identification and Recognition Using Radial Basis Function

... In this Paper, we have presented a writer identification and recognition system that utilizes Radial Basis Function (RBF) in the Off-line mode. Our approach is text independent and uses text lines as basic ...

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Learning Methods of Radial Basis Function Neural Network

Learning Methods of Radial Basis Function Neural Network

... Radial Basis Function Neural Network ( RBF ) is widely used now; it can solve the following problems: the small sample, nonlinear, dimension and local ...

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Training of Radial Basis Function Using Particle Swarm Optimization

Training of Radial Basis Function Using Particle Swarm Optimization

... Broomhead and Lowe in 1988 use the RBF in the design of Neural Network. It is based on moving or directed along the radius. Radial Basis Function emerged as a variant of artificial neural networks in late ...

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A RADIAL BASIS FUNCTION PARTITION OF UNITY METHOD FOR TRANSPORT ON THE SPHERE

A RADIAL BASIS FUNCTION PARTITION OF UNITY METHOD FOR TRANSPORT ON THE SPHERE

... radial basis function partition of unity method (RBF-PUM) for solving the transport equation on the surface of the sphere and applied it to several benchmark problems from the ...

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Unified Noise Reduction using Adaptive Radial Basis Function

Unified Noise Reduction using Adaptive Radial Basis Function

... radial basis function acts as a unified filter for ...radial basis function neural network to learn the correction of the noisy ...kernel function is applied to reconstruct the local ...

7

Radial Basis Function Networks for Conversion of Sound Spectra

Radial Basis Function Networks for Conversion of Sound Spectra

... Radial Basis Function Networks (RBFN) is proposed for the modeling of the spectral changes (or conversions) related to the control of important sound parameters, such as pitch or ...

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A radial basis function WENO method with stencil adaptivity

A radial basis function WENO method with stencil adaptivity

... radial basis function Weighted Essentially Non-Oscillatory (WENO) reconstruction is used to develop a stencil adaptivity strategy that will be coupled with the WENO ...

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Symmetric Radial Basis Function Network Equaliser

Symmetric Radial Basis Function Network Equaliser

... In this paper, we re-visit nonlinear equalisation using the ra- dial basis function (RBF) network [1]-[5]. It is well-known that equalisation can be viewed as a classification problem and the optimal ...

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Preconditioning for radial basis function partition of unity methods

Preconditioning for radial basis function partition of unity methods

... radial basis function (RBF) methods are of interest for solving par- tial differential equations due to attractive convergence properties, flexibility with respect to geometry, and ease of ...

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Face Recognition by Radial Basis Function Network (RBFN)

Face Recognition by Radial Basis Function Network (RBFN)

... Radial Basis Function Network (RBFN) is an attractive solution for the researchers who are working on the field of machine recognition, pattern recognition and computer ...radial basis ...

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Computation of transient viscous flows using indirect radial basis function networks

Computation of transient viscous flows using indirect radial basis function networks

... Abstract: In this paper, an indirect/integrated radial-basis-function network (IRBFN) method is further developed to solve transient partial dif- ferential equations (PDEs) governing fluid flow problems. ...

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An optimal experimental design perspective on redial basis function regression

An optimal experimental design perspective on redial basis function regression

... radial basis function regression that reveals striking similarities with the traditional optimal experimental design ...radial basis function net- work, are very similar and often identical to ...

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Compact integrated radial basis function modelling of particulate suspensions

Compact integrated radial basis function modelling of particulate suspensions

... radial basis function (CIRBF) approximations for the spatial discretisation, and (iii) second-order Adams-Bashforth/Crank- Nicolson algorithms for the temporal ...delta function is employed to ...

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Radial Basis Function Network Assisted Wide Band Beamforming

Radial Basis Function Network Assisted Wide Band Beamforming

... A classic assumption in the field of multiple antenna based beamformers is that the number of receiver antennas is at least as high as the number of users supported, because the performance of ’over-loaded’ beamformers ...

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Nonlinear Image Restoration Using a Radial Basis Function Network

Nonlinear Image Restoration Using a Radial Basis Function Network

... radial basis function network (RBFN), has received considerable attention ...smooth function that achieves a good tradeo ff be- tween fidelity to the data and ...of basis functions is set to ...

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Classifying ReachOut posts with a radial basis function SVM

Classifying ReachOut posts with a radial basis function SVM

... The ReachOut clinical psychology shared task challenge addresses the problem of provid- ing an automatic triage for posts to a sup- port forum for people with a history of men- tal health issues. Posts are classified ...

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Radial Basis Function Assisted Turbo Equalization

Radial Basis Function Assisted Turbo Equalization

... P REVIOUS TURBO equalization (TEQ) research has invoked component equalizer implementations using the soft-output Viterbi algorithm (SOVA) [1], [2], the optimal maximum a posteriori (MAP) algorithm [2], [3], and linear ...

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CutIGA with basis function removal

CutIGA with basis function removal

... the basis function removal approach based on simply eliminating basis functions that has a small intersection with the domain in the context of isogeometric analysis, more precisely we employ ...

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Function Approximation Using Robust Radial Basis Function Networks

Function Approximation Using Robust Radial Basis Function Networks

... Resistant training in radial basis function (RBF) networks is the topic of this paper. In this paper, one modification of Gauss-Newton training algorithm based on the theory of robust regression for dealing ...

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Approximation of function and its derivatives using radial basis function networks

Approximation of function and its derivatives using radial basis function networks

... radial basis function based on a set of 250 test ...approximate function obtained from all networks are quite low and hence the global shape of the orig- inal function is well captured as ...

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