In many cases, the best way to understand a dynamical system is to construct a "phase portrait" diagramming its steady states and their basins of attraction.
Figure 1 Flip bifurcation diagram of model (3.7) for (hin[2,3]) with local amplification to (a) Figure 2 Phase portraits diagram of model (3.7) for various h corresponding to Figure 1 Figure 3 Maximal Lyapunov exponents corresponding to Figure 1.
Figure 4 N-S bifurcation diagram of model (3.7) for (alphain [0.8,0.99]) with local amplification to (a) Figure 5 Phase portraits diagram of model (3.7) for various α corresponding to Figure 4 Figure 6 Maximal Lyapunov exponents corresponding to Figure 4.
The fundamental properties of such systems are investigated by means of equilibrium points, phase portrait, bifurcation diagram and Lyapunov exponents.
In order to analyze a variety of periodic and chaotic phenomena, we employ several numerical techniques such as phase portrait, bifurcation diagram, and Lyapunov exponents.
What is the outcome of the simulation (specific values, time courses, phase portraits, bifurcation diagram)?
Which experimental results correspond to the outcome of the simulation (specific values, time courses, phase portraits, bifurcation diagram).
The dynamical properties of this new system are identified by using phase portraits, bifurcation diagrams, and the Lyapunov exponents spectra.
The numerical simulations are performed to verify the analytical results in the form of phase portraits, bifurcation diagrams and Lyapunov exponents.
For both models, the dynamical behaviour of the system is illustrated by phase plane portraits, bifurcation diagrams, power spectra and Poincaré sections.
