期刊
MATHEMATICAL AND COMPUTER MODELLING
卷 37, 期 7-8, 页码 829-847出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/S0895-7177(03)00088-8
关键词
neural networks; fuzzy neural networks; interpolation functions; mathematical neurons; learning algorithms
Mathematical essence and structures of feedforward neural networks are researched in detail in this paper. First of all, interpolation mechanism of feedforward neural networks is exposed, so we can more clearly understand why a feedforward network is of approximation. For example, a well-known conclusion for arbitrarily a continuous function, there exists a three-layer forward neural network such that the network can approximate the function to within any given precision. It, in fact, is regarded as a natural result of interpolation representation. Then the learning algorithms of feedforward neural networks are discussed by some new ideas. (C) 2003 Elsevier Science Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据