  By means of the concepts of factorial moment, return map and NM estimator, we
analyze some responses of a HH neuron to various types of spike-train inputs.
The corresponding fractal dimensions and values of NM estimators can describe
the correlation characteristics quantitatively. It is found that all the
intervals of successive output spikes may obey a power-law for some conditions.
And in time scale the output series for a HH model for each type of inputs is
correlated with typical correlation length and correlation strength. These
power-law and correlation characteristics may be useful in the coding and
decoding process of HH neurons. These concepts may distinguish different inputs
quantitatively.
  PACS number(s): 87.18.Sn, 84.35.+i, 05.45.Tp
