Symbolic local information transfer

@article{Nakajima2014SymbolicLI,
  title={Symbolic local information transfer},
  author={Kohei Nakajima and Taichi Haruna},
  journal={The European Physical Journal Special Topics},
  year={2014},
  volume={222},
  pages={437-455}
}
  • K. Nakajima, T. Haruna
  • Published 25 June 2013
  • Computer Science
  • The European Physical Journal Special Topics
Recently, the permutation-information theoretic approach has been used in a broad range of research fields. In particular, in the study of high-dimensional dynamical systems, it has been shown that this approach can be effective in characterizing global properties, including the complexity of their spatiotemporal dynamics. Here, we show that this approach can also be applied to reveal local spatiotemporal profiles of distributed computations existing at each spatiotemporal point in the system… 
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References

SHOWING 1-10 OF 72 REFERENCES
Local information transfer as a spatiotemporal filter for complex systems.
TLDR
A measure of local information transfer, derived from an existing averaged information-theoretical measure, namely, transfer entropy, is presented, providing the first quantitative evidence for the long-held conjecture that the emergent traveling coherent structures known as particles are the dominant information transfer agents in cellular automata.
The local information dynamics of distributed computation in complex systems
TLDR
A complete information-theoretic framework to quantify these operations on information, and in particular their dynamics in space and time, is applied to cellular automata, and delivers important insights into the fundamental nature of distributed computation and the dynamics of complex systems.
The organization of intrinsic computation: complexity-entropy diagrams and the diversity of natural information processing.
TLDR
This work uses complexity-entropy diagrams to analyze intrinsic computation in a broad array of deterministic nonlinear and linear stochastic processes, including maps of the interval, cellular automata, and Ising spin systems in one and two dimensions, Markov chains, and probabilistic minimal finite-state machines.
Symbolic transfer entropy rate is equal to transfer entropy rate for bivariate finite-alphabet stationary ergodic Markov processes
TLDR
The Transfer entropy rate and its permutation analogue, the symbolic transfer entropy rate, are considered and it is shown that they are equal for any bivariate finite-alphabet stationary ergodic Markov process.
Permutation Complexity and Coupling Measures in Hidden Markov Models
TLDR
The equalities between various information theoretic complexity and coupling measures and their permutation analogues are shown and the following two results are shown within the realm of hidden Markov models with ergodic internal processes.
Permutation complexity of spatiotemporal dynamics
TLDR
This letter proposes to extend the study of permutation complexity to spatiotemporal systems, by applying some of its tools to a time series obtained by coarse-graining the dynamics and to state vectors at fixed times, considering the latter as sequences.
Differentiating information transfer and causal effect
TLDR
It is shown that causal information flow is a primary tool to describe the causal structure of a system, while information transfer can then be used to describes the emergent computation on that causal structure.
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