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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Imperial Coll London, Blackett Lab, London SW7 2AZ, England
London Inst Math Sci, 35a South St Mayfair, London W1K 2XF, EnglandImperial Coll London, Blackett Lab, London SW7 2AZ, England
Wan, Kwok Ho
Dahlsten, Oscar
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Imperial Coll London, Blackett Lab, London SW7 2AZ, England
London Inst Math Sci, 35a South St Mayfair, London W1K 2XF, England
Univ Oxford, Clarendon Lab, Parks Rd, Oxford OX1 3PU, England
South China Univ Sci & Technol SUSTech, Shenzhen, Peoples R ChinaImperial Coll London, Blackett Lab, London SW7 2AZ, England
Dahlsten, Oscar
Kristjansson, Hler
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Imperial Coll London, Blackett Lab, London SW7 2AZ, England
London Inst Math Sci, 35a South St Mayfair, London W1K 2XF, EnglandImperial Coll London, Blackett Lab, London SW7 2AZ, England
Kristjansson, Hler
Gardner, Robert
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Imperial Coll London, Blackett Lab, London SW7 2AZ, England
London Inst Math Sci, 35a South St Mayfair, London W1K 2XF, EnglandImperial Coll London, Blackett Lab, London SW7 2AZ, England
Gardner, Robert
Kim, M. S.
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