Radial Basis Function
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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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 ...
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Radial Basis Function Neuroscaling Algorithms for Efficient Facial Image Recognition
... A Radial basis function neural network-based probabilistic principal component analysis (RBFNN-PPCA) on image recognition based on facial recognition was ...
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Logic Programming In Radial Basis Function Neural Networks
... step function within feedforward neural networks (Hölldobler and Kalinke, 1994; Hitzler et ...continuous function on a compact subset of R can be uniformly approximated by MLPs with sigmoid units in the ...
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Face Recognition by Radial Basis Function Network (RBFN)
... [11] Tiantian Xie, Hao Yu and Bogdan Wilamowski, “Comparison between Traditional Neural Networks and Radial Basis Function Networks”Industrial Electronics(ISIE), 2011 IEEE International Symposium on, ...
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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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Radial Basis Function Networks for Conversion of Sound Spectra
... of Radial Basis Function Network, RBFN, and is a special case of feedforward neural network which ex- hibit high performances in nonlinear curve-fitting (approxi- mation) problems ...The radial ...
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Unified Noise Reduction using Adaptive Radial Basis Function
... to radial basis function architecture. Radial basis function uses adaptive form of Gaussian basis function which supports the local correlation of pixels for ...
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Radial basis function neural network for software engineering measures A survey
... (Radial Basis Function) and SVM has some secure relationship among them where they both are identified in many applications like in face verification, optical character recognition, text ...
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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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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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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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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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Nonlinear Image Restoration Using a Radial Basis Function Network
... generalized radial basis function network (GRBFN) and a regu- larization ...blurring function itself, the existence of the in- verse of the blurring process does not need to be ...
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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 ...
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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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Maximum 2-satisfiability in radial basis function neural network
... meaning function for feed- forward neural networks with three layers. Radial Basis Function (RBFNN) is a feedforward ANN that contains hidden layers which requires the calculation of centre ...
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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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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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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 ...
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