Modified Hebbian auto-adaptive impulse neural circuits
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 1561-1563 |
| Journal / Publication | Electronics Letters |
| Volume | 26 |
| Issue number | 19 |
| Publication status | Published - 1 Jan 1990 |
| Externally published | Yes |
Link(s)
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.
In: Electronics Letters, Vol. 26, No. 19, 01.01.1990, p. 1561-1563.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
