Publications with Abstracts by Alfred Hübler (1999)
* Publications in journals with a strict referee process
- * M. Sperl, A Chang, N. Weber, A. Hübler, Hebbian Learning in the Agglomeration of Conducting Particles, Phys.Rev.E. 59, 3165-3168 (1999)
Abstact: The Hebbian learning rule is a fundamental concept in the learning of a neuronal net, where a frequently used connection of two neutrons is continually reinforced. We study the properties of self- assembling connections of conducting particles in a dielectic liquid, and find that the strength of the connection between the different electrodes represents a memory for the history of the system. Optimal parameters and sequences of simulation for effective training are determined. We discuss a future application of our results for the implementation of a nonvolatile neuronal network based on self-assembling nanowires on a semiconductor surface.
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