Visualizing long vectors of measurements by use of the Hilbert curve
Data Analysis, Statistics and Probability
2015-11-30 v1 Computational Physics
Abstract
The use of Hilbert curves to visualize massive vector of data is revisited following previous authors. The Hilbert curve mapping preserves locality and makes meaningful representation of the data. We call such visualization as Hilbert plots. The combination of a Hilbert plot with its Fourier transform allows to identify patterns in the underlying data sequence. The use of different granularity representation also allows to identify periodic intervals within the data. Data from different sources are presented: periodic, aperiodic, logistic map and 1/2-Ising model. A real data example from the study of heartbeat data is also discussed.
Keywords
Cite
@article{arxiv.1508.03817,
title = {Visualizing long vectors of measurements by use of the Hilbert curve},
author = {E. Estevez-Rams and C. Perez-Davidenko and B. Aragón Fernández and R. Lora-Serrano},
journal= {arXiv preprint arXiv:1508.03817},
year = {2015}
}
Comments
Accepted at Computer Physics Communications