Pattern Recognition Letters - Special issue on fuzzy set technology in pattern recognition
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Expert Systems with Applications: An International Journal
Flood forecasting using radial basis function neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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
Nonlinear blind source separation using a radial basis function network
IEEE Transactions on Neural Networks
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In this paper, we develop a new design strategy of Radial Basis Function (RBF) neural network and provide a comprehensive design methodology and algorithmic setup supporting its development. The architecture of the network is fully reflective of the structure encountered in the training data which are granulated with the aid of clustering techniques. More specifically, the output space is granulated with use of FCM clustering while the information granules in the multidimensional input space are formed by using a so-called context-based Fuzzy C-Means which takes into account the structure being already formed in the output space. A series of numeric studies exploiting synthetic data and data from the Machine Learning Repository provide a detailed insight into the nature of the algorithm and its parameters as well as offer some comparative analysis.