In this paper, we will give a new type of fixed point theorem for non - self - mapping in a complete metrically convex metric space.
本文给出在完备度量凸空间上非自映射的一类新的不动点定理。
The test proves that if prototype space mapping is reasonable, then this unsupervised learning ANN has good self - learning function. It has good application in engineering.
试验表明，只要样本空间映射合理，这种自组织无监督的神经网络具有很好的自学习功能，在工程中具有广泛的应用前景。
In this paper, some results are obtained for a continuous self-mapping of topo - logical space with zero entropy.
本文给出了空间连续自映射拓扑熵等于零的几个充分条件。
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