radial basis function based approach
An Approach to Measure Pronunciation Similarity in Second Language Learning Using Radial Basis Function Kernel
... the second, third and fourth lines show the results of the RBF kernel-based nPAD Θ ℓ r b f for σ 2 = 0.002, 0.001 and 0.0005, respectively. These are shown in table as Θ r b f ℓ 250 , Θ ℓ r b f500 and Θ ℓ r b f ...
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Radial Basis Function Neural Networks : A Review
... structures, radial basis network (RBF), general regression neural network (GRNN) and probabilistic neural network (PNN) on the Wisconsin breast cancer data ...evolutionary radial basis ...
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Addendum to: An Approach to Hierarchical Clustering via Level Surfaces and Convexity
... level-sets approach to hierarchical clustering where the underlying density function is formed as the sum of identical radial basis functions centered at the data points in either Euclidean or ...
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Support Vector approach by using Radial Kernel Function for Prediction of Software Maintenance Effort on the basis of Multivariate Approach
... kernel function has been selected, one can practically work in spaces of any dimension without any significant additional computational cost, since feature mapping is never effectively ...
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Heart Disease Diagnosis Based on Deep Radial Basis Function Kernel Machine
... years Radial Basis Function (RBF) Kernel Machines have been used in Machine Learning tasks, but there are certain flaws that prevent their usage in some up-to-date applications ...RBF based on ...
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Classifying ReachOut posts with a radial basis function SVM
... The labeled data set, while of decent size, and rep- resentative of what can reasonably be done by anno- tators in a small amount of time, is not so large that the SVM-based approach, with the features ...
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Radial Basis Function Networks for Conversion of Sound Spectra
... of 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 ...is ...
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Radial Basis Function Assisted Turbo Equalization
... This approach is dif- ferent from that of the RBF-based equalizer having a feedfor- ward order of , where the received sequence of -symbols is required each time the a posteriori LLR is evalu- ated using ...
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Approximation of function and its derivatives using radial basis function networks
... the function and its deriva- ...usual approach is to try a multiple of networks with possibly dierent structures and values for training parameters and the \best" net- work (based on some ...
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Analysis of back propagation and radial basis function neural networks for handover decisions in wireless communication
... activation function is superior for classification applications ...primarily based models are linear in parameters and thus assure convergence to their ideal values for specific network ...
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Computation of transient viscous flows using indirect radial basis function networks
... This approach allows a precise representation of the interface whereas its main drawback is the severe deforma- tion of the mesh as the interface ...ond approach, which is based on fixed grids, in- ...
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Application of Radial Basis Function Network for Content Based Image Retrieval
... Content Based Image Retrieval The Classifier is used to reduce the huge amount of the data base and will offer the semantically similar images whereas the optimizer optimizes the semantic difference between the ...
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System Design of a Computer-Based Clinical Decision Support System Management by Using Radial Basis Function Approach
... To select a model, we should study affordable and compatible methods with the limited resources of the hospital. Also we should maintain the quality and healthcare services that it needs to make a balance between health ...
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Radial basis function (RBF)-based interpolation and spreading for the immersed boundary method
... techniques based on smooth mesh deformation ...classical approach is to solve the problem equations on a uniform cartesian grid (Eulerian) for both solid and fluid ...
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Heady et al., 1990(Sundaram, 1996). Intrusion detection is classified into two
... traffic based on the deviations from the normal patterns, where the normal patterns are constructed from the statistical measures of the system features ...combined approach can be used as an efficient ...
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Prediction of Daily Network Traffic based on Radial Basis Function Neural Network
... an approach for predicting daily network traffic using artificial neural networks (ANN), namely radial basis function neural network (RBFNN) ...
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Adaptive Radial Basis Function Detector for Beamforming
... beamformer based on the minimum mean square error (L-MMSE) solution ...the radial basis function (RBF) network [17]-[19] and other kernel models [20]-[25] have been applied to solve this ...
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A novel integrated approach of relevance vector machine optimized by imperialist competitive algorithm for spatial modeling of shallow landslides
... Among these, SVM is also a powerful method for landslide modeling [6]. The SVM method uses statistical learning theory to find an optimum linear hyper-plane to separate two classes of landslide and non-landslide. In this ...
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Numerical solution for the fluid flow between active elastic walls
... codes based on the one- dimensional Integrated Radial Basis Function Networks (1 d-irbfn ) ...faster approach and efficiency ...
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A generalised finite difference scheme based on compact integrated radial basis function for flow in heterogeneous soils
... difference approach based on compact integrated radial basis function (CIRBF) stencils for solv- ing highly nonlinear Richards equation governing fluid movement in hetero- geneous ...
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