Adaptive speech recognition with evolving connectionist systems
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Spoken language analysis, modeling and recognition-statistical and adaptive connectionist approaches
Evolutionary Design of Nearest Prototype Classifiers
Journal of Heuristics
Improving multiclass pattern recognition with a co-evolutionary RBFNN
Pattern Recognition Letters
Fast structural learning of distance-based neural networks
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Speed-up of the R4-rule for distance-based neural network learning
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Dual-population based coevolutionary algorithm for designing RBFNN with feature selection
Expert Systems with Applications: An International Journal
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The nearest-neighbor multilayer perceptron (NN-MLP) is a single-hidden-layer network suitable for pattern recognition. To design an NN-MLP efficiently, this paper proposes a new evolutionary algorithm consisting of four basic operations: recognition, remembrance, reduction, and review. Experimental results show that this algorithm can produce the smallest or nearly smallest networks from random initial ones