# Quantifying Statistical Interdependence by Message Passing on GraphsPart II: Multidimensional Point Processes

@article{Dauwels2009QuantifyingSI, title={Quantifying Statistical Interdependence by Message Passing on GraphsPart II: Multidimensional Point Processes}, author={Justin Dauwels and François B. Vialatte and Theophane Weber and Toshimitsu Musha and Andrzej Cichocki}, journal={Neural Computation}, year={2009}, volume={21}, pages={2203-2268} }

- Published 2009 in Neural Computation
DOI:10.1162/neco.2009.11-08-899

Stochastic event synchrony is a technique to quantify the similarity of pairs of signals. First, events are extracted from the two given time series. Next, one tries to align events from one time series with events from the other. The better the alignment, the more similar the two time series are considered to be. In Part I, the companion letter in this issue, one-dimensional events are considered; this letter concerns multidimensional events. Although the basic idea is similar, the extension… CONTINUE READING

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