## Relative order defines a topology for recurrent networks
Swanston, D.J., Kambhampati, C., Manchanda, S., Tham, M. and Warwick, K.
(1995)
Full text not archived in this repository. It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1049/cp:19950564 ## Abstract/SummaryThis paper uses techniques from control theory in the analysis of trained recurrent neural networks. Differential geometry is used as a framework, which allows the concept of relative order to be applied to neural networks. Any system possessing finite relative order has a left-inverse. Any recurrent network with finite relative order also has an inverse, which is shown to be a recurrent network.
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