Non-Linear Back-propagation: Doing Back-Propagation withoutDerivatives of the Activation Function

Publication: Research - peer-reviewJournal article – Annual report year: 1997

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The conventional linear back-propagation algorithm is replaced by a non-linear version, which avoids the necessity for calculating the derivative of the activation function. This may be exploited in hardware realizations of neural processors. In this paper we derive the non-linear back-propagation algorithms in the framework of recurrent back-propagation and present some numerical simulations of feed-forward networks on the NetTalk problem. A discussion of implementation in analog VLSI electronics concludes the paper.
Original languageEnglish
JournalI E E E Transactions on Neural Networks
Publication date1997
Volume8
Journal number6
Pages1321-1327
ISSN1045-9227
StatePublished

ID: 5784692