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review2.txt
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review2.txt
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Dear Authors,
Congratulations to the Authors on such a very interesting and at the same time very difficult manuscript. Written at a very high level for very advanced readers, at least in the field of neuronal spike train, stochastics, statistics and chaos. Starting a detailed assessment from the beginning, it is necessary to emphasize the comprehensive and impeccable introduction to the issue of the construction of a novel kind of power spectrum, which is the inter-spike spectrum. Moreover, the Authors explained the algorithm in great detail (in numerous pictures). By the way, also with outer -spike. Literature examples below review. The illustrations of tau-recurrence rate based spectrum (Fig. 1) and the transformation diagrams of the series of Dirac delta function (Fig. 2), including the two proposed inter-spikes spectrum, deserve emphasis. A small remark - regarding verse 35: what will be with stochastic resonance, because we are dealing with impulse disturbances.? Chapter 2 presents the signal decomposition into set of appropriate basis functions using Dirac comb. Here, too, we can distinguish a graphic representation of the decomposition procedure (Fig. 3). Nevertheless, the Authors could cite a position in the literature that discusses other methods of decomposition. In Chapter 3, the Authors presented three serious examples of the use of inter-spike spectrum in combination with the tau-RR with detailed procedures. usage. The theoretical basics are presented in Appendix A to Appendix D. A small note on Appendix C: It would be interesting to present an inter-spike spectra also for one of the nonlinear systems from Duffing, Mackey-Glass or Chen systems. Summary: The manuscript is so interesting and correctly written that some of the comments could be considered optional.
Yours sincerely, Reviewer
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10) Simone Orcioni, Alessandra Paffi, Francesca Apollonio and Micaela Liberti: Revealing Spectrum Features of Stochastic Neuron Spike Trains. Mathematics 2022, 10(20), 3826; https://doi.org/10.3390/math10203826 (registering DOI) - 16 Oct 2022 IMPORTANT