In this paper, a natural extension of the Lempel–Ziv complexity for several finite-time sequences, defined on finite size alphabets is proposed. Some results on the defined joint Lempel–Ziv complexity are given, as well as properties in connection with the Lempel–Ziv complexity of the...

The extremization of the information-theoretic measures (Fisher information, Shannon entropy, Tsallis entropy), which complementary describe the spreading of the physical states of natural systems, gives rise to fundamental equations of motion and/or conservation laws. At times, the associated...

The scaling properties of various composite information-theoretic measures (Shannon and Rényi entropy sums, Fisher and Onicescu information products, Tsallis entropy ratio, Fisher–Shannon product and shape complexity) are studied in position and momentum spaces for the non-relativistic...

We calculate the time-dependent Shannon (Sx and Sp) entropy and Fisher (Fx and Fp) information of three log-periodic oscillators. We obtain a general expression for Sx,p and Fx,p in the state n=0 in terms of ρ, a c-number quantity satisfying a nonlinear differential equation. For two out of...

The Dirac-delta-like quantum-mechanical potentials are frequently used to describe and interpret numerous phenomena in many scientific fields including atomic and molecular physics, condensed matter and quantum computation. The entropy and complexity properties of potentials with one and two...

Recently, the importance of correctly designed computational experiments for testing algorithms has been a subject of extended discussions. Whenever real-world data is lacking, generated data sets provide a substantive methodological tool for experiments. Focused research questions need to base...

Information measures have been used in the context of nonlinear systems presenting abrupt complexity changes and related to nonlinear time series analysis. In this study, complexity measures such as Shannon entropy, q-entropy and their associated divergences have been added to a robust speech...