Estimating the Entropy Rate of Spike Trains via Lempel-Ziv Complexity

@article{Amig2004EstimatingTE,
  title={Estimating the Entropy Rate of Spike Trains via Lempel-Ziv Complexity},
  author={Jos{\'e} Mar{\'i}a Amig{\'o} and Janusz Szczepanski and Elek Wajnryb and Maria V. Sanchez-Vives},
  journal={Neural Computation},
  year={2004},
  volume={16},
  pages={717-736}
}
Normalized Lempel-Ziv complexity, which measures the generation rate of new patterns along a digital sequence, is closely related to such important source properties as entropy and compression ratio, but, in contrast to these, it is a property of individual sequences. In this article, we propose to exploit this concept to estimate (or, at least, to bound from below) the entropy of neural discharges (spike trains). The main advantages of this method include fast convergence of the estimator (as… CONTINUE READING

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