Algorithms for clustering data
Algorithms for clustering data
Algorithms for better representation and faster learning in radial basis function networks
Advances in neural information processing systems 2
Fuzzy regression wiht radial basis function network
Fuzzy Sets and Systems
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
On the Kernel Widths in Radial-Basis Function Networks
Neural Processing Letters
Stochastic simulations of web search engines: RBF versus second-order regression models
Information Sciences—Informatics and Computer Science: An International Journal
Evolving RBF neural networks for time-series forecasting with EvRBF
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Informatics and computer science intelligent systems applications
Fast learning in networks of locally-tuned processing units
Neural Computation
Improved batch fuzzy learning vector quantization for image compression
Information Sciences: an International Journal
Fuzzy connectivity clustering with radial basis kernel functions
Fuzzy Sets and Systems
Visual RBF network design based on Star Coordinates
Advances in Engineering Software
On training radial basis function neural networks using optimal fuzzy clustering
MED '09 Proceedings of the 2009 17th Mediterranean Conference on Control and Automation
A classification technique based on radial basis function neural networks
Advances in Engineering Software
IEEE Transactions on Neural Networks
A new approach to fuzzification of memberships in cluster analysis
MDAI'05 Proceedings of the Second international conference on Modeling Decisions for Artificial Intelligence
On cluster validity for the fuzzy c-means model
IEEE Transactions on Fuzzy Systems
Conditional fuzzy clustering in the design of radial basis function neural networks
IEEE Transactions on Neural Networks
A new clustering technique for function approximation
IEEE Transactions on Neural Networks
Robust and adaptive backstepping control for nonlinear systems using RBF neural networks
IEEE Transactions on Neural Networks
High-speed face recognition based on discrete cosine transform and RBF neural networks
IEEE Transactions on Neural Networks
| Hi-index | 0.20 |
This paper introduces a novel clustering-based algorithm to train Gaussian type radial basis function neural networks. In contrast to existing approaches, we develop a specialized learning strategy that combines the merits of fuzzy and crisp clustering. Crisp clustering is a fast process, yet very sensitive to initialization. On the other hand, fuzzy clustering reduces the dependency on initialization; however, it constitutes a slow learning process. The proposed strategy aims to search for a trade-off among these two potentially different effects. The produced clusters possess fuzzy and crisp areas and therefore, the final result is a hybrid partition, where the fuzzy and crisp conditions coexist. The hybrid clusters are directly involved in the estimation process of the neural network's parameters. Specifically, the center elements of the basis functions coincide with cluster centers, while the respective widths are calculated by taking into account the topology of the hybrid clusters. To this end, the network's design becomes a fast and efficient procedure. The proposed method is successfully applied to a number of experimental cases, where the produced networks prove to be highly accurate and compact in size.