Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 98 for “"Radial Basis Function"”.
-
Iterative Techniques for Radial Basis Function Interpolation
The problem of interpolating functions comes up naturally in many areas of applied mathematics and natural sciences. Radial basis function methods provide an interpolant to values of a real function of $\textit{d}$ variables and are highly useful in many applications, especially if the function …
-
Radial basis function based meshless methods for fluid flow problems
… with the development of meshless methods using radial basis functions for solving fluid flow problems. The advantage of meshless methods over traditional mesh-based methods is that they make use of a scattered set of collocation points in the physical domain and no connectivity information is …
-
Analysing rounding data using radial basis function neural networks model
Unspecified counting practices used in a data collection may create rounding to certain ‘based’ number that can have serious consequences on data quality. Statistical methods for analysing missing data are commonly used to deal with the issue but it could actually aggravate the problem. Rounded …
-
A radial basis function approach to financial time series analysis
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.
-
A radial basis function approach to pricing and hedging options incorporating transaction costs
Nonparametric methods of pricing options have been available for some time, providing a viable alternative to traditional parametric methods. A general class of methods known as learning networks has been making significant inroads in option pricing literature. This thesis will adopt McLoone's …
-
Efficient facial animation integrating Euclidean and geodesic distance-based algorithms into radial basis function interpolation.
… animation with this technology together with Radial Basis Function (RBF) interpolation, covering a review of Euclidean and geodesic distance-based algorithms, and proposing a hybrid approach that tries to take the advantages of the two previous methods aided by pre-processed distance data to …
-
Real-time identification of an unmanned quadcopter flight dynamics using fully tuned radial basis function network
… configuration. This study utilised a fully tuned radial basis function (RBF) neural network to obtain a minimal structure and avoid pre-determining the number of hidden neurons by introducing the adding and pruning neuron strategy. The prediction performance of the proposed fully tuned RBF was …
-
A Radial Basis Function Approach to a Color Image Classification Problem in a Real Time Industrial Application
In this thesis, we introduce a radial basis function network approach to solve a color image classification problem in a real time industrial application. Radial basis function networks are employed to classify the images of finished wooden parts in terms of their color and species. Other …
-
The Application of a Radial Basis Function Morphing Technique to a Validated Full Human Body Finite Element Model
… finite element model and use that model as a basis for the development of a large male model.
-
Improvement of pavement mechanistic-empirical design (PMED) virtual weather station interpolation model using radial basis function - Tennessee case study
… model interpolation technique and that by a Radial Basis Function (RBF). RBF interpolation showed very fast error convergence with the increase in number of interpolation data as compared to the gravity model. Contour plots emphasized the quality of interpolation where the RBF model produced …
-
Land cover mapping through optimizing remote sensing data for SVM classification
… used SVMs include linear, polynomial and radial basis function (i.e. Gaussian) classifiers.
-
A comparative evaluation of data mining classification techniques on medical trauma data
… Probablilistic Neural Networks, and the Radial Basis Function) are able to correctly classify cases into the different categories of an outcome measure from a given set of input variables (i.e. estimate their classification accuracy) on a common database.
-
An evaluation of support vector machines in consumer credit analysis
… credit. The support vector machine using a radial basis function (RBF) kernel is compared to a previous implementation of a decision tree machine learning model. The dataset used for evaluation was provided by a large bank and includes relevant consumer-level data, including transactions and …
-
Computing Eigenmodes of Elliptic Operators on Manifolds Using Radial Basis Functions
… compared against existing alternative methods. Radial Basis Function (RBF)-based methods allow one to obtain interpolation and differentiation matrices easily by using scattered data points. We derive expressions for such matrices for the Laplace-Beltrami operator via so-called Reilly’s formulas …
-
Characterizing complex time-series from the scaling of prediction error
… error. We use the global modeling technique of radial basis function approximation to build models from a state-space reconstruction of a time series that otherwise appears complicated or random (i.e. aperiodic, irregular). Prediction error as a function of prediction horizon is obtained from …
-
An RBFN-based system for speaker-independent speech recognition
… compared. Phone recognition is performed using a radial basis function network (RBFN). Dynamic time warping (DTW) is used for word recognition. The TIMIT database is used to design and test the automatic speech recognition (ASR) system. Several feature sets using mel-scale filter bank (MSFB), …
-
Approximating differentiable relationships between delay embedded dynamical systems with radical basis functions
… dynamical systems. The basic approach is to fit radial basis function maps between time delay embeddings of manifolds. We have shown that under certain conditions these maps are generically diffeomorphisms, and can be analysed to determine whether or not the manifolds in question are …
-
A Fuzzy/Neural Approach to Cost Prediction with Small Data Sets
… final cost prediction. Finally, method 3 uses a radial basis function network (RBFN) to predict the engine test cost.
-
Spatially varying threshold models for the automated segmentation of radiodense tissue in digitized mammograms
… a digitized mammogram. The algorithm employs a radial basis function neural network in order to segment the breast tissue region from the remainder of the X-ray. A spatially varying Neyman-Pearson threshold is used to calculate the percentage of radiodense tissue and compensate for the effects …
Page 1 of 5