A robust model based on space-partitioning method

A new model, called the space-partitioning multilayer perceptron (SP-MLP), is proposed in this paper to resolve classification problems. The number of first-hidden-layer units is determined adaptively, and we introduce a new sub-algorithm to improve the robustness of the network. The results of expe...

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Bibliographic Details
Published inNeural Information Processing: 6th International Conference, 1999 Vol. 3; pp. 992 - 997 vol.3
Main Authors Liming Zhang, Weiping Fan
Format Conference Proceeding
LanguageEnglish
Published IEEE 1999
Subjects
Analytical models
Convergence
Handwriting recognition
Multilayer perceptrons
Neural networks
Neurons
Partial response channels
Partitioning algorithms
Robustness
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ISBN9780780358713
0780358716
DOI10.1109/ICONIP.1999.844671

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Summary:A new model, called the space-partitioning multilayer perceptron (SP-MLP), is proposed in this paper to resolve classification problems. The number of first-hidden-layer units is determined adaptively, and we introduce a new sub-algorithm to improve the robustness of the network. The results of experiments show that the SP-MLP is more robust than other models. The issue of generalization is also discussed in this paper.
ISBN:9780780358713
0780358716
DOI:10.1109/ICONIP.1999.844671