Título: A Brief Account on Morphological Perceptron with Competitive Layer Trained by a Certain Genetic Algorithm
Autores: Valente, Raul Ambrozio; Valle, Marcos Eduardo
Resumo: Lattice computing models such as the morphological neural networks and fuzzy neurocomputing models are becoming increasingly important with the advent of granular computing. In particular, the morphological perceptron with competitive learning (MP/CL), introduced by Sussner and Esmi, exhibited satisfactory classification results in some well known classification problems. On the downside, the MP/CL is subject to overfitting in which the network learns singular characteristics from the training data. In this paper, we propose a learning strategy based on a certain genetic algorithm to circumvent the overfitting problem of MP/CL. Computational experiments revealed that the novel model can achieve similar classification results but using a smaller number of hidden neurons.
Palavras-chave: Neural networks; morphological perceptron; classification problem; genetic algorithm
Código DOI: 10.21528/CBIC2013-197
Artigo em pdf: bricsccicbic2013_submission_197.pdf
Arquivo BibTex: bricsccicbic2013_submission_197.bib