Database Reference
In-Depth Information
Fig. 13.2
1: SICK
1:
30
1
1
1
1:
20
1
1:
10
0.00
50.00
100.00
150.00
200.00
Time
Fig. 13.3
13.1.2 Detecting and Interpreting Chaos
The only way to technically determine the presence of chaos in our model is to be
able to calculate the so-called Lyapunov exponent for the model. If this exponent is
greater than zero, the model is chaotic. The exponent can be calculated using data
from the model on the rate of separation of nearest neighboring points though time.
It seems that at our level of modeling, however, we can observe the model results.
