𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Stabilization of Hebbian neural nets by inhibitory learning

✍ Scribed by Paul Easton; Peter E. Gordon


Publisher
Springer-Verlag
Year
1984
Tongue
English
Weight
820 KB
Volume
51
Category
Article
ISSN
0340-1200

No coin nor oath required. For personal study only.


πŸ“œ SIMILAR VOLUMES


Improved bidirectional retrieval of spar
✍ Friedrich T. Sommer; GΓΌnther Palm πŸ“‚ Article πŸ“… 1999 πŸ› Elsevier Science 🌐 English βš– 288 KB

The Willshaw model is asymptotically the most efficient neural associative memory (NAM), but its finite version is hampered by high retrieval errors. Iterative retrieval has been proposed in a large number of different models to improve performance in auto-association tasks. In this paper, bidirecti

Stability analysis of neural net control
✍ Thomas Feuring; James J. Buckley; Wolfram-M. Lippe; Andreas Tenhagen πŸ“‚ Article πŸ“… 1999 πŸ› Elsevier Science 🌐 English βš– 810 KB

Neural networks can only be trained with a crisp and finite data set. Therefore, the approximation quality of a trained network is hard to verify. So, a common way in proving stability of a trained neural net controller is to demonstrate the existence of a Lyapunov function. In this article we propo

Controlling low-dimensional chaos: Deter
✍ Michael Funke; Michael Herrmann; Ralf Der πŸ“‚ Article πŸ“… 1997 πŸ› John Wiley and Sons 🌐 English βš– 191 KB

A simple but efficient neural-network-based algorithm for non-linear control of chaotic systems is presented. The scheme relies on the method proposed by Ott et al. (Phys. Rev. ΒΈett., 64, 1196 (1990)) to stabilize unstable periodic orbits by appropriate small changes in a control parameter. In contr

Activity-dependent regulation of recepti
✍ FrοΏ½gnac, Yves ;Shulz, Daniel E. πŸ“‚ Article πŸ“… 1999 πŸ› John Wiley and Sons 🌐 English βš– 196 KB

Most algorithms currently used to model synaptic plasticity in self-organizing cortical networks suppose that the change in synaptic efficacy is governed by the same structuring factor, i.e., the temporal correlation of activity between pre-and postsynaptic neurons. Functional predictions generated