Conclusion


 

    The use those methods to detect non-linear coupling is very wide since it can be applyed to any kind of experimental data as long as the stationarity of the data is assured. Moreover the method is fairly robust against noise contamination because of the density estimation step where data is "averaged" on a small range of the phase space. However, the power spectrum is still the time series analysis tool that is first used and it will last for a while. The non-linear coupling detection is aimed to help in "hard conditions" like the pathological cases of the cardiorespiratory interaction.
    From a personnal point of view, this hands-on dealing with nonlinearity, chaos and hydrodynamic instabilities made me "think in another way". Moreover, the use of these "chaotic mathematics" to represent phenomena that doesn't seem to behave in a deterministic way end the diversity of its application's fields really impressed me. The main link between those phenomena is their apparent "chaotic" behavement.
 
 
 
 
 


Bibliography


 
 

[1]    Detection of Nonlinear Coupling and its Application to Cardiorespiratory Interaction, Guillermo J. Ortega, Diego A. Golombek

[2]    Hydrodinamic Instabilities, Olivier Thual