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Summary: Technische Universit¨at HamburgHarburg
Technische Informatik I
A Learning Algorithm for Structured Invariant
Neural Networks
Interner Bericht 5/96
Sabine Kr¨oner
Technische Informatik I
Technische Universit¨at HamburgHarburg
D21071 Hamburg
email: kroener@tuharburg.d400.de
September 1996
Abstract
Structured multilayer feedforward neural networks gain more and more importance
in speech and image processing applications. The characteristic of structured neural
networks is that apriori knowledge about the task to be performed is directly built
into their architecture by the use of nodes with shared weight vectors. Usually these
networks are trained with a modified backpropagation algorithm. However, due to the
constraints on the weight vectors it is difficult to find suitable initialization values, and
often the algorithm fails to converge.
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