Non-Linear Back-propagation: Doing Back-Propagation withoutDerivatives of the Activation Function
Publication: Research - peer-review › Journal article – Annual report year: 1997
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 language | English |
|---|---|
| Journal | I E E E Transactions on Neural Networks |
| Publication date | 1997 |
| Volume | 8 |
| Journal number | 6 |
| Pages | 1321-1327 |
| ISSN | 1045-9227 |
| State | Published |
ID: 5784692