Electronic nose based tea quality standardization
Neural Networks - 2003 Special issue: Advances in neural networks research IJCNN'03
Neural and Wavelet Network Models for Financial Distress Classification
Data Mining and Knowledge Discovery
Modelling of a magneto-rheological damper by evolving radial basis function networks
Engineering Applications of Artificial Intelligence
International Journal of Systems Science
Nonlinear multiantenna detection methods
EURASIP Journal on Applied Signal Processing
An error-counting network for pattern classification
Neurocomputing
Increasing classification efficiency with multiple mirror classifiers
Expert Systems with Applications: An International Journal
A novel ensemble of classifiers for microarray data classification
Applied Soft Computing
A POD-Based Center Selection for RBF Neural Network in Time Series Prediction Problems
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II
Feature Bispectra and RBF Based FM Signal Recognition
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
International Journal of Systems Science
A Versatile Hyper-Ellipsoidal Basis Function for Function Approximation in High Dimensional Space
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Fast and efficient training of RBF networks
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
A fast multi-output RBF neural network construction method
Neurocomputing
A very fast neural learning for classification using only new incoming datum
IEEE Transactions on Neural Networks
A hybrid particle swarm optimization and its application in neural networks
Expert Systems with Applications: An International Journal
Remote sensing image fusion based on adaptive RBF neural network
ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II
Improving radial basis function networks for human face recognition using a soft computing approach
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
Bayesian radial basis function neural network
IDEAL'05 Proceedings of the 6th international conference on Intelligent Data Engineering and Automated Learning
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Orthogonal relief algorithm for feature selection
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Privacy preserving neural networks in iris signature feature extraction
Proceedings of the 5th International Conference on PErvasive Technologies Related to Assistive Environments
Neural Processing Letters
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For classification applications, the role of hidden layer neurons of a radial basis function (RBF) neural network can be interpreted as a function which maps input patterns from a nonlinear separable space to a linear separable space. In the new space, the responses of the hidden layer neurons form new feature vectors. The discriminative power is then determined by RBF centers. In the present study, we propose to choose RBF centers based on Fisher ratio class separability measure with the objective of achieving maximum discriminative power. We implement this idea using a multistep procedure that combines Fisher ratio, an orthogonal transform, and a forward selection search method. Our motivation of employing the orthogonal transform is to decouple the correlations among the responses of the hidden layer neurons so that the class separability provided by individual RBF neurons can be evaluated independently. The strengths of our method are double fold. First, our method selects a parsimonious network architecture. Second, this method selects centers that provide large class separation.