前向神经网络交叉覆盖算法的一种改进

An Ameliorating to Alternative Covering Design Algorithm of Multi-layer Neural Networks

对前向神经网络交叉覆盖算法进行了分析,在此基础上提出了一种改进的交叉覆盖神经网络模型,并给出其算法。实例表明这种改进算法不但可以进一步提高交叉覆盖算法的训练速度,而且可以减少拒识样本数,提高识别的精度,对样本分布较稀疏的模式识别问题具有较强的实用价值。

Present an ameliorating model of the alternative covering design of multilayer neural networks based on the analysis of the alternative covering design algorithm and give the steps of the algorithm. Instances show that this kind of algorithm can improve the accuracy of recognition and reduce the number of the test samples that can't be covered by the spherical neighborhood gained before.Also it has the quite strong practical value to model recognition of the scattered samples distribution.