| 样本复杂性估计算法优化神经网络结构 |
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| 引用本文： | 杨英.样本复杂性估计算法优化神经网络结构[J].广东交通职业技术学院学报,2009,8(2):45-48. |
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| 作者姓名： | 杨英 |
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| 作者单位： | 广东交通职业技术学院,广东广州,510650 |
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| 摘 要： | 在神经网络结构寻优中，样本复杂性估计算法是期望在寻优之前先对问题的规模有所估计，进而根据规模给出一个结构，使之不用从最小结构开始一一尝试。频域分析及仿真实验结果均证明了此算法的有效性。
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| 关 键 词： | 神经网络 结构优化 样本复杂性 LMBP算法 |
Samples Complexity Estimation Algorithm Optimizes Structure of Artificial Neural Network |
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| YANG Ying.Samples Complexity Estimation Algorithm Optimizes Structure of Artificial Neural Network[J].Journal of Guangdong Communication Polytechnic,2009,8(2):45-48. |
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| Authors: | YANG Ying |
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| Institution: | YANG Ying (Guangdong Communications Polytechnic,Guangzhou 510650,China) |
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| Abstract: | In the artificial neural network（ANN） structure optimization, the sample complexity estimation algorithm expects that the scale to the question is estimated to some extent first during the optimization of the neural network structure, and then provides a structure according to the scale, make it not need to begin a try fi＇om the minimum structure The frequency analysis and the simulation results of this method have proved its effectiveness. |
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| Keywords: | neural network structure optimization samples complexity LMBP algorithm |
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