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An explanation of reasoning neural networks

✍ Scribed by R.R. Tsaih

Publisher
Elsevier Science
Year
1998
Tongue
English
Weight
693 KB
Volume
28
Category
Article
ISSN
0895-7177

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✦ Synopsis

tioning Neural Networks (RN) adopts the layered feedforward network structure, and its learning algorithm belongs to the weight-and-structure-change category of learning algorithm. In this paper, we firstly explain that, in the layered feedforward network, the essential characteristic of the mapping between two consecutive layers is the level-adjacent mapping, in which level-adjacent patterns in the previous-layer spsce are mapped to similar patterns in the latter-layer space. Then, we explain how RN's learning algorithm handles the undesired predicaments associated with the back propagation learning algorithm.

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