19 papers · ranked by Valyu relevance
Thomas F. Varley
In the 21st century, many of the crucial scientific and technical issues facing humanity can be understood as problems associated with understanding, modelling, and ultimately controlling complex systems: systems comprised of a large number of non-trivially interacting components whose collective behaviour can be…
David Ellerman
The logical basis for information theory is the newly developed logic of partitions that is dual to the usual Boolean logic of subsets. The key concept is a "distinction" of a partition, an ordered pair of elements in distinct blocks of the partition. The logical concept of entropy based on partition logic is the…
Emanuela Furfaro, Fushing Hsieh, Philip Broadbridge
Individual subjects’ ratings neither are metric nor have homogeneous meanings, consequently digital- labeled collections of subjects’ ratings are intrinsically ordinal and categorical. However, in these situations, the literature privileges the use of measures conceived for numerical data. In this paper, we discuss the…
Akira Kamatsuka, Takahiro Yoshida
This study focuses on conditional entropy frameworks based on the Kolmogorov--Nagumo (KN) mean. First, $(η, ψ)$-KN averaging (\texttt{EPKNAVG}), a KN-mean extension of the $η$-averaging (\texttt{EAVG}) framework for $(η, F)$-entropies, is introduced and proven to be equivalent to \texttt{EAVG} under suitable…
Christoph Adami
Information is a precise concept that can be defined mathematically, but its relationship to what we call "knowledge" is not always made clear. Furthermore, the concepts "entropy" and "information", while deeply related, are distinct and must be used with care, something that is not always achieved in the literature.…
Maria Ribeiro, Teresa Henriques, Luísa Castro, André Souto + 4 more
'Luís Antunes' 'Cristina Costa-Santos' 'Andreia Teixeira' 'Miguel Rubi'] About 160 years ago, the concept of entropy was introduced in thermodynamics by Rudolf Clausius. Since then, it has been continually extended, interpreted, and applied by researchers in many scientific fields, such as general physics, information…
Andreia Teixeira, André Souto, Luís Antunes, Philip Broadbridge
There is no generally accepted definition for conditional Tsallis entropy. The standard definition of (unconditional) Tsallis entropy depends on a parameter $α$ that converges to the Shannon entropy as $α$ approaches 1. In this paper, we describe three proposed definitions of conditional Tsallis entropy suggested in…
Reginald D. Smith
There is no closed form analytical equation or quick method to calculate probabilities based only on the entropy of a signal or process. Except in the cases where there are constraints on the state probabilities, one must typically derive the underlying probabilities through search algorithms. These become more…
Christoph Adami
Information is a precise concept that can be defined mathematically, but its relationship to what we call ‘knowledge’ is not always made clear. Furthermore, the concepts ‘entropy’ and ‘information’, while deeply related, are distinct and must be used with care, something that is not always achieved in the literature.…
Arthur Prat-Carrabin, Florent Meyniel, Rava Azeredo da Silveira
An abundant literature reports on ‘sequential effects’ observed when humans make predictions on the basis of stochastic sequences of stimuli. Such sequential effects represent departures from an optimal, Bayesian process. A prominent explanation posits that humans are adapted to changing environments, and erroneously…
Heinz-Jürgen Schmidt, Thomas Bröcker
In order to reconcile the entropy reduction of a system through external interventions that are linked to a measurement with the second law of thermodynamics, there are two main proposals: (i) The entropy reduction is compensated by the entropy increase as a result of the measurement on the system ("Szilard…
Abigail J. Ameri, Zachary A. Lewis
Neurospora crassa has been an important model organism for molecular biology and genetics for over 60 years. N. crassa has a complex life cycle, with over 28 distinct cell types and is capable of transcriptional responses to many environmental conditions including nutrient availability, temperature, and light. To…
David P. Shorten, Richard E. Spinney, Joseph T. Lizier
Transfer entropy (TE) is a widely used measure of directed information flows in a number of domains including neuroscience. Many real-world time series in which we are interested in information flows come in the form of (near) instantaneous events occurring over time, including the spiking of biological neurons, trades…
Authors not listed
Gibbs’ paradox—the apparent discontinuity in mixing entropy for gases of varying similarity and the seeming reversibility of mixing-separation cycles—has resisted fully satisfactory resolution for 150 years. We present a solution based on categorical state theory, which posits that physical con f igurations are…
Dhurata Nebiu, Hiqmet Kamberaj
Symbolic 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…
Stephanie Wankowicz, James Fraser
During protein folding, proteins transition from a disordered polymer into a globular structure, markedly decreasing their conformational degrees of freedom and consequently leading to a substantial reduction in entropy. Nonetheless, folded proteins still retain significant entropy as they fluctuate between the…
Stephanie Wankowicz, James Fraser
During protein folding, proteins transition from a disordered polymer into a globular structure, markedly decreasing their conformational degrees of freedom and consequently leading to a substantial reduction in entropy. Nonetheless, folded proteins still retain significant entropy as they fluctuate between the…
Mohsen Farshad
The energy and entropy, expressed in free energy, determine the behavior of a system. Therefore, infinite knowledge of these two quantities leads to precise prediction of the system's trajectories. Here, we study how the energy and entropy affect the distribution of a two-component system in a box. First, using a…
Emilio Salinas, Terrence R Stanford
Intuitively, combining multiple sources of evidence should lead to more accurate decisions than considering single sources of evidence individually. In practice, however, the proper computation may be difficult, or may require additional data that are inaccessible. Here, based on the concept of conditional…