Results 21 to 30 of about 18,808 (242)

Identifying and Ranking Factors Affecting Earnings Response Coefficient [PDF]

Iranian Journal of Accounting, Auditing & Finance, 2022
One of the most critical questions after financial statements is why market responses differ from companies with almost similar statements. This research aims to answer this question by identifying factors affecting the earnings response coefficient.
Seyed Mohsen Mousavi, Meysam Arabzadeh, Mohamad Alipoor, Omid Faraji, Aliakbar Farzinfar   +4 more
doaj   +1 more source

Geometric Partition Entropy: Coarse-Graining a Continuous State Space

Entropy, 2022
Entropy is re-examined as a quantification of ignorance in the predictability of a one dimensional continuous phenomenon. Although traditional estimators for entropy have been widely utilized in this context, we show that both the thermodynamic and ...
Christopher Tyler Diggans, Abd AlRahman R. AlMomani   +1 more
doaj   +1 more source

Shannon Entropy Used for Feature Extractions of Optical Patterns in the Context of Structural Health Monitoring

Entropy, 2023
A novelty signal processing method is proposed for a technical vision system (TVS). During data acquisition of an optoelectrical signal, part of this is random electrical fluctuation of voltages.
Wendy Garcia-González, Wendy Flores-Fuentes, Oleg Sergiyenko, Julio C. Rodríguez-Quiñonez, Jesús E. Miranda-Vega, Daniel Hernández-Balbuena   +5 more
doaj   +1 more source

A step beyond Tsallis and Renyi entropies [PDF]

, 2005
Tsallis and R\'{e}nyi entropy measures are two possible different generalizations of the Boltzmann-Gibbs entropy (or Shannon's information) but are not generalizations of each others.
Abe, Frank, Frank, Gell-Mann, Jizba, Khinchin, Kolmogorov, Lesche, Marco Masi, Nagumo, Naudts, Rényi, Rényi, Sharma, Sharma, Tsallis   +15 more
core   +1 more source

Entropy, Shannon’s Measure of Information and Boltzmann’s H-Theorem

Entropy, 2017
We start with a clear distinction between Shannon’s Measure of Information (SMI) and the Thermodynamic Entropy. The first is defined on any probability distribution; and therefore it is a very general concept.
Arieh Ben-Naim
doaj   +1 more source

Conceptual Inadequacy of the Shannon Information in Quantum Measurements [PDF]

, 2001
In a classical measurement the Shannon information is a natural measure of our ignorance about properties of a system. There, observation removes that ignorance in revealing properties of the system which can be considered to preexist prior to and ...
A. Bartana, A. Feinstein, A. Rényi, Anton Zeilinger, C. E. Shannon, C. Tsallis, D. J. Tannor, D. K. Faddeev, D. M. Greenberger, E. Schrödinger, E. T. Jaynes, E. T. Jaynes, I. Ivanovic, I. M. Gelfand, J. Lee, J. Lee, J. S. Bell, M. A. Horne, M. O. Scully, P. Hausladen, R. A. Fisher, R. Horodecki, R. Horodecki, S. Abe, S. Kochen, T. J. Herzog, W. K. Wootters, Č. Brukner, Časlav Brukner   +28 more
core   +2 more sources

On Estimation of Shannon’s Entropy of Maxwell Distribution Based on Progressively First-Failure Censored Data

Stats
Shannon’s entropy is a fundamental concept in information theory that quantifies the uncertainty or information in a random variable or data set.
Kapil Kumar, Indrajeet Kumar, Hon Keung Tony Ng   +2 more
doaj   +1 more source

A Note on Distance-based Graph Entropies

Entropy, 2014
A variety of problems in, e.g., discrete mathematics, computer science, information theory, statistics, chemistry, biology, etc., deal with inferring and characterizing relational structures by using graph measures. In this sense, it has been proven that
Zengqiang Chen, Matthias Dehmer, Yongtang Shi   +2 more
doaj   +1 more source

An Assessment of Hermite Function Based Approximations of Mutual Information Applied to Independent Component Analysis

Entropy, 2008
At the heart of many ICA techniques is a nonparametric estimate of an information measure, usually via nonparametric density estimation, for example, kernel density estimation.
Julian Sorensen
doaj   +1 more source

Statistical Mechanics Analysis of LDPC Coding in MIMO Gaussian Channels [PDF]

, 2007
Using analytical methods of statistical mechanics, we analyse the typical behaviour of a multiple-input multiple-output (MIMO) Gaussian channel with binary inputs under LDPC network coding and joint decoding.
Chung J, Cover T, David Saad, de Miguel R, Edwards S F, Hartmann A K, Iba Y, Kabashima Y, Kirkpatrick S, Luby M G Mitzenmacher M Shokrollahi M A Spielman D A Stemann V, MacKay D, Murayama T, Mézard M, Nishimori H, Roberto C Alamino, Sourlas N, Tanaka T Saad D, Vicente R, Vicente R, Yeap B L   +19 more
core   +2 more sources