Artificial Neural Net Attractors
J. C. Sprott
Department of Physics, University
of Wisconsin, Madison, WI 53706, USA
Aesthetically appealing patterns are produced by the dynamical behavior
of artificial neural networks with randomly chosen connection strengths.
These feed-forward networks have a single hidden layer of neurons and a
single output, which is fed back to the input to produce a scalar time
series that is always bounded and often chaotic. Sample attractors
are shown and simple computer code is provided
to encourage experimentation.
Ref: J. C. Sprott, Comput. & Graphics
The complete paper is available in PDF format.
Return to Sprott's Books and Publications.
Fig. 1. A feed-forward neural network with D inputs, N
neurons, and a single output that is fed back to the input.
Fig. 2. Sample neural network attractors.
Fig. 3. Additional neural network attractors.
The computer source code nnet256.bas
from the article is available along with an executable version nnet256.exe.
Many more images of this type are available.