|CRP Toolbox Reference|
PurposeFind the optimal embedding dimension by means of false nearest neighbours.
y=fnn(x) computes the vector y of the amount of false nearest neighbours (FNN) as a function of the embedding dimension.
y=fnn(x,m), where m is a scalar, computes the FNN up to dimension m. The defeault is m=10.
y=fnn(x,m,t), where t is a scalar, computes the FNN using embedding delay t. The defeault is t=1.
y=fnn(x,m,t,r,s), where r and s are scalars, applies the neighbourhood criterion r and the size of the neighbourhood s. the defeault is r=2 and s=Inf.
y=fnn(x,m,t,r,s,n), where n is a scalar, uses n random samples for the determination of the FNNs. This speeds up the estimation, especially for long data series. The default is n=length(x) if the data length is smaller than 500, else n=200.
fnn(...) without any output arguments opens a GUI for interactively changing the parameters.
By using the GUI, the FNNs can be stored into the workspace.
fnn without any arguments calls a demo (the same as the example below).
ReferencesKennel, M. B., Brown, R., Abarbanel, H. D. I.: Determining embedding dimension for phase-space reconstruction using a geometrical construction, Phys. Rev. A, 45, 1992.