In this paper, we describe how Ehresmann connections can be used to study certain properties of feedforward neural networks. Essentially, we calculate a Lie group approximation to the structure of the inverse image set above a certain point in the output space and this structure can then be locally transported to the inverse image above a, neighbouring point in the output space by means of an Ehresmann connection. This enables us to find a continuous approximation to the underlying topological structure of the data from discrete data pairs (input/output pairs). (C) 1999 Elsevier Science Ltd. All rights reserved.
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Changsha Univ Sci & Technol, Sch Hydraul & Environm Engn, Changsha 410014, Peoples R China
Changsha Univ Sci & Technol, Sch Comp & Commun Engn, Changsha 410014, Peoples R ChinaChangsha Univ Sci & Technol, Sch Hydraul & Environm Engn, Changsha 410014, Peoples R China
Wang, Jin
Zou, Yongsong
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Changsha Univ Sci & Technol, Sch Hydraul & Environm Engn, Changsha 410014, Peoples R ChinaChangsha Univ Sci & Technol, Sch Hydraul & Environm Engn, Changsha 410014, Peoples R China
Zou, Yongsong
Lim, Se -Jung
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Honam Univ, Div Convergence, AI Liberal Arts Studies, Gwangju Si 62399, South KoreaChangsha Univ Sci & Technol, Sch Hydraul & Environm Engn, Changsha 410014, Peoples R China