Modified Hebbian auto-adaptive impulse neural circuits

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)1561-1563
Journal / PublicationElectronics Letters
Volume26
Issue number19
Publication statusPublished - 1 Jan 1990
Externally publishedYes

Abstract

Artificial neural networks learn by adapting interconnection weights. A generalised weight adaptation expression for associative learning has been implemented using synapse circuits based on floating gate devices. A reinforcement depending on the correlation of a synapse input and a neuronal output is used. The circuits also illustrate the influence of the conditioning stimuli amplitude on the conditioning rate.

Citation Format(s)

Modified Hebbian auto-adaptive impulse neural circuits. / Nintunze, N.; Wu, A.

In: Electronics Letters, Vol. 26, No. 19, 01.01.1990, p. 1561-1563.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal