Where R is the normalized rabbit population and K is the stability
factor.
In the above series, the all important K determines the fate of the
rabbit population. Of course this is not literally true or
rabbits around the world would be cornering the market on K's. This is
just a real world analogy, please don't take it
literally. What makes this interesting is the effect of the value
of K. The series can decay, go into positive feedback, stabilize,
oscillate or go pseudo random. Such a simple equation, such
effects. The magic number is 3.57. Not 42 but 3.57. We
shall see.
How to analyze this data? Tens of
points will show asymptotic
behaviour, maybe oscillations. But how random is random? What
happens in the transition regions? Listen to it! Take lots of
data and turn it into an audio file for the computer
to play. Listen to this, as K steps from
3.4 to 3.9.
|

|
The "K" Effect
& Sounds
| K |
Details |
Listen |
| <-2 |
Oscillations increase in amplitude, positive feedback. |
(nothing to hear) |
| -2 to
-1.6 |
Noise. |
K = -1.9, -1.8, -1.7 |
| -1.6 to
-1.57 |
Oscillations with sidetones and noise. |
K = -1.6 |
| -1.57 to
-1.5 |
Stable oscillation with sidetones. |
K = -1.5 |
| -1.5 to
-1 |
Stable oscillation. |
K = -1.4, -1.3, -1.2, -1.1 |
| -1 to 0 |
Decaying oscillation |
K = -1.0 |
| 0 to 1 |
Exponential decay to 0. |
(nothing to hear) |
| 1 to 3 |
Stabilizes at a value between 0 and 2/3. |
(nothing to hear) |
| 3 to 3.5 |
Stable oscillation. |
K = 3.4, 3.45, 3.5 |
| 3.5 to
3.57 |
Stable oscillation with sidetones. |
K = 3.55 |
| 3.57 to
3.6 |
Oscillations with sidetones and noise. |
K = 3.6 |
| 3.6 to
3.85 |
Noise. |
K = 3.65, 3.7, 3.75, 3.8 |
| 3.85 |
Stable oscillation. |
K = 3.85 |
| 3.85 to 4 |
Noise. |
K = 3.9, 3.95 |
| >4 |
Oscillations increase in amplitude, positive feedback. |
(nothing to hear) |
|