Generalization of back-propagation to recurrent neural networks

Fernando J. Pineda

Research output: Contribution to journalArticlepeer-review

512 Scopus citations


An adaptive neural network with asymmetric connections is introduced. This network is related to the Hopfield network with graded neurons and uses a recurrent generalization of the rule of Rumelhart, Hinton, and Williams to modify adaptively the synaptic weights. The new network bears a resemblance to the master/slave network of Lapedes and Farber but it is architecturally simpler.

Original languageEnglish (US)
Pages (from-to)2229-2232
Number of pages4
JournalPhysical Review Letters
Issue number19
StatePublished - 1987
Externally publishedYes

ASJC Scopus subject areas

  • General Physics and Astronomy


Dive into the research topics of 'Generalization of back-propagation to recurrent neural networks'. Together they form a unique fingerprint.

Cite this