Monday, July 06, 20093:00 PM - 4:00 PMCNLS Conference Room|
Self-assembling fractal particle networks: Physical systems with an understanding?
Alfred HublerUniversity of Illinois
We study the agglomeration of conducting particles in between
high-voltage electrodes experimentally. We find that the emergent
fractal networks are stable and stationary. The degree distribution of
the network is highly reproducible: 22% of the particles are
endpoints, 22% of the particles are three-fold branching points, and
the rest of the particles have degree two. The networks are binary
without closed loops. The power consumption decreases during the
growth of the network, if the electrical current is kept constant. The
response of the networks to an external stimulus is consistent with
Hebb's learning rule. Therefore they can be considered as hardware
implementations of neural nets. We discuss potential applications in
computing and engineering.
Host: Vadas Gintautas