GENERALIZATION STUDY FOR A ROBUST ESTIMATION METHOD OF NEURAL NETS

Liu Guangyuan; Liao Xiaofeng; Yu Juebang; Qiu Yuhui

Volume 21 Issue 1

Jan. 1999

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Article Navigation > Journal of Electronics & Information Technology > 1999 > 21(1): 128-131

Liu Guangyuan, Liao Xiaofeng, Yu Juebang, Qiu Yuhui. GENERALIZATION STUDY FOR A ROBUST ESTIMATION METHOD OF NEURAL NETS[J]. Journal of Electronics & Information Technology, 1999, 21(1): 128-131.

Citation:

Liu Guangyuan, Liao Xiaofeng, Yu Juebang, Qiu Yuhui. GENERALIZATION STUDY FOR A ROBUST ESTIMATION METHOD OF NEURAL NETS[J]. Journal of Electronics & Information Technology, 1999, 21(1): 128-131.

Liu Guangyuan, Liao Xiaofeng, Yu Juebang, Qiu Yuhui. GENERALIZATION STUDY FOR A ROBUST ESTIMATION METHOD OF NEURAL NETS[J]. Journal of Electronics & Information Technology, 1999, 21(1): 128-131.

Citation:

Liu Guangyuan, Liao Xiaofeng, Yu Juebang, Qiu Yuhui. GENERALIZATION STUDY FOR A ROBUST ESTIMATION METHOD OF NEURAL NETS[J]. Journal of Electronics & Information Technology, 1999, 21(1): 128-131.

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GENERALIZATION STUDY FOR A ROBUST ESTIMATION METHOD OF NEURAL NETS

Received Date: 1997-04-22
Rev Recd Date: 1998-06-05
Publish Date: 1999-01-19

Abstract

Abstract

In this paper, the Cauchy function is taken as a new target function of neural network accordings to the robustness theorem of statistics. Under the same network parameter conditions the BP net is trained using both mean squresand Cauchy target function firstly, then the net is tested by data sets including small Gaussian noises and outliers separately. Simulation results indicate that the network has both faster convergence speed and better performance against outliers after learning with robust target function.

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References(1)

References

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