Original Contribution: Model-based neural networks

Authors:
Terry M. Caelli;David McG. Squire;Tom P. J. Wild
Affiliations:
-;-;-
Venue:
Neural Networks
Year:
1993

Citing 4
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Abstract

In this paper we show how neural networks can be formulated in terms of various parameterised connection models which explicitly encode desired properties of the target system. Such a modelling approach to neural networks raises issues about their relationships to other technologies such as Adaptive Filtering and Principal Components Analysis. The benefits of this approach can be a significant decrease in the parameter space, improved generalisation, and a learning procedure which guarantees a priori specified invariance constraints.