A Fast Learning Algorithm of Feedforward Neural Networks 

Based on Screening Samples Dynamically

Sheng Shou-zhao; Wang Dao-bo; Huang Xiang-hua

Volume 27 Issue 11

Nov. 2005

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Article Navigation > Journal of Electronics & Information Technology > 2005 > 27(11): 1818-1820

Sheng Shou-zhao, Wang Dao-bo, Huang Xiang-hua. A Fast Learning Algorithm of Feedforward Neural Networks Based on Screening Samples Dynamically[J]. Journal of Electronics & Information Technology, 2005, 27(11): 1818-1820.

Citation:

Sheng Shou-zhao, Wang Dao-bo, Huang Xiang-hua. A Fast Learning Algorithm of Feedforward Neural Networks Based on Screening Samples Dynamically[J]. Journal of Electronics & Information Technology, 2005, 27(11): 1818-1820.

Citation:

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A Fast Learning Algorithm of Feedforward Neural Networks Based on Screening Samples Dynamically

Received Date: 2004-06-04
Rev Recd Date: 2004-09-09
Publish Date: 2005-11-19

Abstract

Abstract

The learning issue of feedforward neural networks whose activation function of hidden neurons satisfies Mercer condition is discussed in theory. The approach to improving learning speed is investigated. Then a fast learning algorithm of feedforward neural networks based on screening samples dynamically is proposed, which improves learning speed, solves the abuses of those learning algorithm based on gradient decent method and has the self-configuring advantage by determining the number of hidden neuron dynamically. The reliability and advantage of the proposed algorithm are illustrated concretely through test.

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References

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