In this paper, the function approximation of Gelenbe Neural Network (GNN) is discussed and it is proved that GNN can approximate any G-type polynomial by using constructional method.
该文研究了G神经网络的函数映射能力，给出了前馈g神经网络映射任意G型多项式的构造性证明。
In this paper, a method for converting GPS height to normal one by means of support vector machine is proposed, and compared with the methods of neural network, polynomial fitting etc.
结合GPS测量和水准测量资料，利用支持向量机方法对GPS高程进行了转换，并与神经网络和多项式拟合等拟合的结果进行了比较，得出了一些有益的结论。
Then we construct a capacity cost network from the debt credit degree network. Finally, by applying minimum cost circulation flow problem, we give a polynomial algorithm for this model.
然后由债务信度网络构造了容量费用网络，利用最小费用循环流问题给出了该模型的一个多项式算法。
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