Pattern Recognition Letters - Special issue on fuzzy set technology in pattern recognition
Time-series forecasting using GA-tuned radial basis functions
Information Sciences—Informatics and Computer Science: An International Journal - Special issue on evolutionary algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Fast Recognition of Musical Genres Using RBF Networks
IEEE Transactions on Knowledge and Data Engineering
Fast learning in networks of locally-tuned processing units
Neural Computation
Symbolic classification, clustering and fuzzy radial basis function network
Fuzzy Sets and Systems
Flood forecasting using radial basis function neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Robust radial basis function neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Conditional fuzzy clustering in the design of radial basis function neural networks
IEEE Transactions on Neural Networks
Reformulated radial basis neural networks trained by gradient descent
IEEE Transactions on Neural Networks
Nonlinear blind source separation using a radial basis function network
IEEE Transactions on Neural Networks
An ART-based construction of RBF networks
IEEE Transactions on Neural Networks
Information Sciences: an International Journal
Designing RBFNNs using prototype selection
MCPR'10 Proceedings of the 2nd Mexican conference on Pattern recognition: Advances in pattern recognition
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part III
A novel training algorithm for RBF neural network using a hybrid fuzzy clustering approach
Fuzzy Sets and Systems
Genetic-Based granular radial basis function neural network
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part I
Fuzzy relation-based polynomial neural networks based on hybrid optimization
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
Hybrid optimized polynomial neural networks with polynomial neurons and fuzzy polynomial neurons
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part I
Information Sciences: an International Journal
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In this study, we develop a design methodology for generalized radial basis function neural networks. In contrast with the plethora of existing approaches, here we promote a development strategy in which a topology of the network is predominantly based upon a collection of information granules formed on a basis of available experimental data. The output space is granulated making use of the K-means clustering while the input space is clustered with the aid of a so-called context-based fuzzy clustering. The number of information granules produced for each context is adjusted so that we satisfy a certain reconstructability criterion that helps us minimize an error between the original data and the ones resulting from their reconstruction involving prototypes of the clusters and the corresponding membership values. In contrast to ''standard'' radial basis function neural networks, the output neuron of the network exhibits a certain functional nature as its connections are realized as local linear or quadratic functions whose location is determined by the values of the context and the prototypes in the input space. The other parameters of these local functions are subject to further parametric optimization. Numeric examples involve some low-dimensional synthetic data and selected data coming from the Machine Learning repository.