gaussianLorenz

DGL of gaussianLorenz

dxdt[0] = S() *( x[1] - x[0] );

dxdt[1] = x[0] *( r() - x[2] ) - x[1];

dxdt[2] = x[0] * x[1] - b() * x[2] +couplingSum() - weightSum()*x[2];

s[0] = sigmaNoise();

Parameter of gaussianLorenz

  • gaussianLorenz_S = 10.0000000000000000;
  • gaussianLorenz_r = 28.0000000000000000;
  • gaussianLorenz_b = 2.6666666000000001;
  • gaussianLorenz_sigmaNoise = 0.0000000000000000;

Example (python-conedy)

import conedy as ns

net = ns.network()

net.addNode(ns.gaussianLorenz())

Example (conedy)

network net;

net.addNode(gaussianLorenz());

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