Tezos

Cellular Neural Network #2

Creator

tz1Yb9mrEBSsv35doLWovF4Dmwy2q4won9oa

Description

Cellular Neural Networks or Cellular Nonlinear Networks (CNN) are similar to Cellular Automata (CA): a grid of cells that evolve in time with local interactions with neighbouring cells. Instead of a finite number of states for each cell (as for the CA) in CNN the cells can assume continuous values given from a chaotic oscillator and the local interactions are due to the coupling of oscillators in neighbouring cells. With CNN is possible to model a number of physical systems described by Partial Differential Equations: Wave propagation, Heat Diffusion, Chemical Reaction-Diffusion and the likes. In this case we have a Lorenz chaotic oscillator on each cell coupled with the 8 neighbouring oscillators. The initial conditions, boundary conditions and coupling constant are chosen in such a way to obtain symmetrical patterns. Here the CNN is rendered as a surface with a colormap from matplotlib (twilight). The rendering is by means of a C++ program with openFrameworks toolkit.

Traits

Tag

openframeworks

Tag

generativegraphics

Tag

ReactionDiffusion

Tag

cplusplus

Tag

coding

Tag

computergraphics

Tag

creativecoding

Tag

neuralnetwork

Token

Contract: KT1RJ6...xton
Token ID: 639680

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