Nonlinear analysis of EAS clusters
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We apply certain methods of nonlinear time series analysis to the extensive air shower clusters found earlier in the data set obtained with the EAS-1000 Prototype array. In particular, we use the Grassberger-Procaccia algorithm to compute the correlation dimension of samples in the vicinity of the clusters. The validity of the results is checked by surrogate data tests and some additional quantities. We compare our conclusions with the results of similar investigations performed by the EAS-TOP and LAAS groups.
4 pages; submitted to Izv. Ros. Akad. Nauk, Ser. Fiz
4 pages; submitted to Izv. Ros. Akad. Nauk, Ser. Fiz