Complex temporal association in neural networks
Models of temporal association in neural networks are generalised to provide mechanisms for decision making and loop control. Systems equipped with these capabilities can handle situations where a succession of states is not unambiguously defined and the system has to choose which out of several, in...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article (Journal) |
| Language: | English |
| Published: |
[1989]
|
| In: |
Journal of physics. A, Mathematical and theoretical
Year: 1989, Volume: 22, Issue: 15, Pages: 3123-3135 |
| ISSN: | 1751-8121 |
| DOI: | 10.1088/0305-4470/22/15/026 |
| Online Access: | Verlag, Volltext: http://dx.doi.org/10.1088/0305-4470/22/15/026 Verlag, Volltext: http://stacks.iop.org/0305-4470/22/i=15/a=026 
|
| Author Notes: | R. Kühn, J.L. van Hemmen and U. Riedel (Sonderforschungsbereich 123, Universitlt Heidelberg) |
| Summary: | Models of temporal association in neural networks are generalised to provide mechanisms for decision making and loop control. Systems equipped with these capabilities can handle situations where a succession of states is not unambiguously defined and the system has to choose which out of several, in principle equivalent, paths it is going to follow. The choice is made on the basis of past experience of the network. No short-term synaptic plasticity is needed. |
|---|---|
| Item Description: | Gesehen am 20.09.2017 Elektronische Reproduktion der Druckausgabe |
| Physical Description: | Online Resource |
| ISSN: | 1751-8121 |
| DOI: | 10.1088/0305-4470/22/15/026 |