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Search results for: ENTROPY, RANDOM VARIABLES, INFORMATION THEORY

  • Marek Czachor prof. dr hab.

  • Discrete random variables in reliability calculations of a reticulated shell

    Implementation of the Point Estimation Method (PEM) in the reliability analysis of a three-dimensional truss structure is presented in the paper. The influence of geometric and material random parameters on the truss load-carrying capacity was investigated. The analysis was performed for different combinations of basic variables. Symmetric and asymmetric cases of snow load were taken to assess the structural reliability. Sensitivity...

  • Detecting coupling directions with transcript mutual information: A comparative study

    Publication

    - DISCRETE AND CONTINUOUS DYNAMICAL SYSTEMS-SERIES B - Year 2019

    Causal relationships are important to understand the dynamics of coupled processes and, moreover, to influence or control the effects by acting on the causes. Among the different approaches to determine cause-effect relationships and, in particular, coupling directions in interacting random or deterministic processes, we focus in this paper on information-theoretic measures. So, we study in the theoretical part the difference between...

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  • Computing algebraic transfer entropy and coupling directions via transcripts

    Publication
    • J. Amigó
    • R. Monetti
    • B. Graff
    • G. Graff

    - CHAOS - Year 2016

    Most random processes studied in nonlinear time series analysis take values on sets endowed with a group structure, e.g., the real and rational numbers, and the integers. This fact allows to associate with each pair of group elements a third element, called their transcript, which is defined as the product of the second element in the pair times the first one. The transfer entropy of two such processes is called algebraic transfer...

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  • Lossless Compression of Binary Trees with Correlated Vertex Names

    Publication

    - Year 2016

    Compression schemes for advanced data structures have become the challenge of today. Information theory has traditionally dealt with conventional data such as text, image, or video. In contrast, most data available today is multitype and context-dependent. To meet this challenge, we have recently initiated a systematic study of advanced data structures such as unlabeled graphs [1]. In this paper, we continue this program by considering...

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