The links between the estimation of the spectral density of a train of δ functions, the estimation of the spectral density of a point process and that of a discrete random signal are established. It shows in particular that it is possible to reduce the estimation of the spectral density of a neural spike train to that of a regularly sampled 0–1 signal with consequent computational advantages. In addition, a technique involving decimation for speeding up the estimation of the spectral density without much additional error is proposed.
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Lago, P.J.A., Jones, N.B. Note on the spectral analysis of neural spike trains. Med. Biol. Eng. Comput. 20, 44–48 (1982). https://doi.org/10.1007/BF02441849
- Spectral analysis
- Spike trains