التفاصيل البيبلوغرافية
| العنوان: |
A Node Pruning Algorithm Based on a Fourier Amplitude Sensitivity Test Method. |
| المؤلفون: |
Lauret, Philippe, Fock, Eric, Mara, Thierry Alex |
| المصدر: |
IEEE Transactions on Neural Networks; Mar2006, Vol. 17 Issue 2, p273-293, 21p, 2 Diagrams, 7 Charts, 22 Graphs |
| مصطلحات موضوعية: |
ARTIFICIAL neural networks, FOURIER analysis, ANALYSIS of variance, STATISTICS, ALGORITHMS, PRODUCT elimination |
| مستخلص: |
In this paper, we propose a new pruning algorithm to obtain the optimal number of hidden units of a single layer of a fully connected neural network (NN). The technique relies on a global sensitivity analysis of model output. The relevance of the hidden nodes is determined by analysing the Fourier decomposition of the variance of the model output. Each hidden unit is assigned a ratio (the fraction of variance which the unit accounts for) that gives their ranking. This quantitative information therefore leads to a suggestion of the most favorable units to eliminate. Experimental results suggest that the method can be seen as an effective tool avail- able to the user in controlling the complexity in NNs. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
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