Radial Basis Function (RBF)
Face Recognition by Radial Basis Function Network (RBFN)
... In this paper, an effective method of face recognition technique has been presented. Image processing algorithms based on Radial basis function network has been used in this paper. This paper ...
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A RADIAL BASIS FUNCTION PARTITION OF UNITY METHOD FOR TRANSPORT ON THE SPHERE
... the 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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Learning enhancement of radial basis function network with particle swarm optimization
... Radial Basis Function (RBF) Networks form a class of Artificial Neural Networks (ANNs), which has certain advantages over other types of ANNs, such as better approximation capabilities, simpler ...
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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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Radial Basis Function Network Assisted Wide Band Beamforming
... In this paper we present a novel Radial Basis Function Net- work (RBFN) assisted wide-band beamformer which is based on the derivation of the Bayesian detector. The proposed re- ceiver structure ...
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Writer Identification and Recognition Using Radial Basis Function
... Handwriting has continued to persist as a means of communication and recording information in day-to-day life even with the introduction of new technologies. Given its ubiquity in human transactions, machine recognition ...
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Radial basis function neural network learning with modified backpropagation algorithm
... Artificial Neural Network (ANN) was developed as a parallel distributed system that is inspired by the biological learning process of the human brain. The primary importance of ANN is its capacity of learning to solve ...
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Unified Noise Reduction using Adaptive Radial Basis Function
... on radial basis functions ...(complex radial basis function neural network) for low order digital channel equalization with an extra parameter to reduce nonlinear ...of radial ...
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Radial Basis Function Finite Difference Approximations of the Laplace-Beltrami Operator
... domains. Radial basis function generated finite differences (RBF-FD) is a recently developed mesh-free method for numerically solving PDEs that is robust, accurate, computationally ef- ficient, and ...
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Preconditioning for radial basis function partition of unity methods
... Meshfree 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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Function Approximation Using Robust Radial Basis Function Networks
... In contrast to MLPs, RBF networks use a localized re- presentation of information. The RBF network requires less computation time for the learning and more compact topology than MLP. The network can be configured with ...
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Training of Radial Basis Function Using Particle Swarm Optimization
... i.e Radial Basis Function by ...radius. Radial Basis Function emerged as a variant of artificial neural networks in late ...a radial activated ...a Radial ...
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Compactly Supported Radial Basis Function Kernels
... The motivation of our work is to construct kernels which have local support and sparse Gram matrices. A closely related work was developed in Achlioptas et al. (2002) which sparsifies the Gram matrix K by randomly ...
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Adaptive Radial Basis Function Detector for Beamforming
... Adaptive beamforming is capable of separating user signals transmitted on the same carrier frequency, and thus provides a practical means of supporting multiusers in a space-division multiple-access scenario [1]–[10]. ...
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Radial Basis Function Assisted Turbo Equalization
... Abstract—This paper presents a turbo equalization (TEQ) scheme, which employs a radial basis function (RBF)-based equalizer instead of the conventional trellis-based equalizer of Douillard et al. ...
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Dynamic Threshold Selection for Sequential Learning in Radial Basis Function Networks
... in Radial Basis Function (RBF) Networks, there is a requirement for dynamic selection of threshold because a constant threshold is inadequate to accommodate functions of varying ...within ...
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Symmetric Radial Basis Function Network Equaliser
... The paper investigates nonlinear equalisation using a novel symmetric radial basis function (RBF) network. By explicitly exploiting the inherently symmetric struc- ture of the optimal Bayesian ...
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Compact integrated radial basis function modelling of particulate suspensions
... integrated radial basis function (CIRBF) approximations for the spatial discretisation, and (iii) second-order Adams-Bashforth/Crank- Nicolson algorithms for the temporal ...delta function is ...
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Stable Gaussian radial basis function method for solving Helmholtz equations
... Helmholtz equation is very important in a variety of science and engineering prob- lems, for example, in physics, technology, geophysics and optical problems. There are several numerical methods for solving the Helmholtz ...
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Design of Hanman Entropy Network from Radial Basis Function Network
... Different learning algorithms have been developed in the literature for train- ing the radial basis function network (RBFN). In this paper, a new neural network named as Hanman Entropy Network (HEN) ...
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