No abstract

AbstractSymbolic Information Flow Measurement software is used to compute the information flow between different components of a dynamical system or different dynamical systems using symbolic transfer entropy. Here, the time series represents the time evolution trajectory of a component of the dynamical system. Different methods are used to perform a symbolic analysis of the time series based on the coarse-graining approach by computing the so-called embedding parameters. Information flow is measured in terms of the so-called average symbolic transfer entropy and local symbolic transfer entropy. Besides, a new measure of mutual information is introduced based on the symbolic analysis, called symbolic mutual information.