| Nonlinear Dynamics, Psychology, and Life Sciences, Vol. 8, Iss. 4, Oct, 2004, pp. 445-478 @2004 Society for Chaos Theory in Psychology & Life Sciences Information Hidden in Signals and Macromolecules I. Symbolic Time-series Analysis Abstract: We describe the conceptual background and practical implementation
of some recently developed techniques for the analysis of symbol
sequences and symbolic time series. We emphasize their associated
software realization, the WinGramm suite of programs, that includes
programs for the calculation of conditional entropies, context-free
grammatical complexity, algorithmic distance and redundancy, as well
as for the generation of surrogates that preserve symbol pairs and
triplets. We demonstrate the usefulness of these programs by means
of two illustrative examples, taken from computational neuroscience.
In the first one, we obtain evidence of the Markovian character of
the cortical inter spike intervals of the rat before penicillin
treatment, and its disappearance afterwards. In the second one,
we extend previous investigations about neural spike-trains generated
by the isolated neuron of the slowly adapting stretch receptor
organ (SAO), in order to classify sequences of different length
of known neural behaviors. We include new spike trains, digitized
employing the optimal partition procedure described by Steuer,
Molgedey, Ebeling, Jim nez-Monta o, (2001). Keywords: symbolic dynamics, time series, conditional entropies, context-free grammatical complexity, surrogates |