A standard radial basis function netw ork
The Matlab Radial Basis Function Toolbox
... Extended precision The MRBFT uses the Multiprecision Computing Toolbox for Matlab (MCT) [1] for its extended precision func- tionality. The MCT enables extended precision data types to be seamlessly used in place of the ...
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Adaptive Radial Basis Function Detector for Beamforming
... a standard RBF detector typically requires significantly more RBF centres than the number of channel output states in order to approximate the Bayesian detector using noisy training data, and often there is a ...
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Function Approximation Using Robust Radial Basis Function Networks
... in radial basis function (RBF) networks is the topic of this ...of function approximation, system identification and control is ...the standard Gauss-Newton ...
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Classifying ReachOut posts with a radial basis function SVM
... 4 Analysis The left axis of figure 1 shows how the perfor- mance changes as a function of the number of ex- amples used. This graph uses the parameter set- tings and class weights from the main submission (i.e |V ...
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Denoising using Self Adaptive Radial Basis Function
... 3.1. Simulation results of SRBF vs ARBF To understand the benefits of proposed adaptiveness in the RBF in comparison to static RBF, learning the behavior of both networks with a noisy image have been considered for 5 ...
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Compact integrated radial basis function modelling of particulate suspensions
... with standard finite- difference results; and (ii) the proposed boundary treatment for the pressure is more effective than conventional direct application of the Neumann boundary ...
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Unified Noise Reduction using Adaptive Radial Basis Function
... adaptive radial basis function acts as a unified filter for ...adaptive radial basis function neural network to learn the correction of the noisy ...kernel function is ...
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Error bound for radial basis interpolation in terms of a growth function
... Radial basis functions are becoming an increasingly popular tool for the approx- imation of functions, see [1, ...the radial basis interpolation in the form going back to ...growth ...
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Maximum 2-satisfiability in radial basis function neural network
... 111 Step 6 Calculate the corresponding RMSE, RSC and CPU time for the network performance RBFNN- MAX2SAT. Models will be evaluated with different numbers of neurons in terms of Root Mean Square Error (RMSE). RMSE is a ...
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An Autonomous Incremental Learning Algorithm for Radial Basis Function Networks
... of radial basis func- tions (RBFs), and 4) determination of RBF centers and ...first function enables AL-RAN to decide the necessity of data normalization from incoming training data, and if it is ...
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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) to address the computational complexity issues with global RBF method [11, ...the standard RBF ...weight function in the ...
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Improv ed Algorithms for Netw ork T opology Discov ery
... the basis of shortest paths, or using a more realistic model of routing in the internet? Would there still be a small but constant per-monitor proba- bility of error? A simpler approach, and one that in any case ...
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Adaptive Radial Basis Function Detector for Beamforming
... ❏ Existing beamforming techniques are linear , and classical beamforming technique is based on minimum mean square error (L-MMSE). ❏ State-of-the-art for linear beamforming is minimum bi[r] ...
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Symmetric Radial Basis Function Network Equaliser
... A sparse M spa -term RBF network can be selected by in- crementally maximising the FRCSM using the OFS proce- dure, outlined in [8],[9]. Let us define the two class sets X ± = { x (k) : d(k) = ± 1 } , and let the number ...
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Symmetric Radial Basis Function Network Equaliser
... ✰ Which exploits prior knowledge on symmetry property of optimal solution, leading to enhanced performance. ❏ Adaptive algorithms for training this symmetric RBF equaliser have been revi[r] ...
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Radial Basis Function Assisted Turbo Equalization
... Radial Basis Function-Assisted Turbo Equalization Mong-Suan Yee, Associate Member, IEEE, Bee Leong Yeap, Member, IEEE, and Lajos Hanzo, Senior Member, IEEE Abstract—This paper presents a turbo ...
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Compactly Supported Radial Basis Function Kernels
... Editor: Abstract The use of kernels is a key factor in the success of many classification algorithms by allow- ing nonlinear decision surfaces. Radial basis function (RBF) kernels are commonly used ...
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Radial Basis Function Neural Networks : A Review
... Radial Basis Function neural networks (RBFNNs) represent an attractive alternative to other neural network ...between function approximation, regularization, noisy interpolation, ...
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Approximation of function and its derivatives using radial basis function networks
... nite basis and all derivatives are obtained as a ...nite basis. Lower derivatives and nally the function itself are obtained by integration which has the prop- erty of damping out or at least ...
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Radial basis function modeling of hourly streamflow hydrograph
... transfer function that controls the generation of output in a neuron, and learning laws that define the relative importance of weights for input to a neuron 共Caudill ...transfer function for the output ...
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