Results 21 to 30 of about 105,087 (310)

Estimating the variance of Shannon entropy [PDF]

Physical Review E, 2021
The statistical analysis of data stemming from dynamical systems, including, but not limited to, time series, routinely relies on the estimation of information theoretical quantities, most notably Shannon entropy. To this purpose, possibly the most widespread tool is provided by the so-called plug-in estimator, whose statistical properties in terms of ...
Ricci, Leonardo, Perinelli, Alessio, Castelluzzo, Michele   +2 more
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Analyzing boron oxide networks through Shannon entropy and Pearson correlation coefficient. [PDF]

Sci Rep
Huang R, Hanif MF, Siddiqui MK, Hanif MF, Petros FB.   +4 more
europepmc   +3 more sources

Shannon entropy: axiomatic characterization and application [PDF]

International Journal of Mathematics and Mathematical Sciences, 2005
We have presented a new axiomatic derivation of Shannon entropy for a discrete probability distribution on the basis of the postulates of additivity and concavity of the entropy function. We have then modified Shannon entropy to take account of observational uncertainty.The modified entropy reduces, in the limiting case, to the form of Shannon ...
C. G. Chakrabarti, Indranil Chakrabarty
doaj   +3 more sources

Adaptive estimation of Shannon entropy [PDF]

2015 IEEE International Symposium on Information Theory (ISIT), 2015
We consider estimating the Shannon entropy of a discrete distribution $P$ from $n$ i.i.d. samples. Recently, Jiao, Venkat, Han, and Weissman, and Wu and Yang constructed approximation theoretic estimators that achieve the minimax $L_2$ rates in estimating entropy.
Han, Yanjun, Jiao, Jiantao, Weissman, Tsachy   +2 more
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On Shannon entropy and its applications

Kuwait Journal of Science, 2023
A brief and intuitive introduction to Shannon entropy is presented, including some of its properties. The application of this measure is exemplified in two different contexts from what was in its genesis: biological diversity and an original study on ...
Paulo Saraiva
doaj   +1 more source

Comparative evaluation of multi-influence factor, Shannon Entropy, and frequency ratio techniques for groundwater potential mapping in the Maze and Zenti catchments, Omo Basin, Ethiopia.

Heliyon
Oyda Y, Hatiye SD, Jothimani M.
europepmc   +2 more sources

On the Characterization of Shannon’s Entropy by Shannon’s Inequality [PDF]

Journal of the Australian Mathematical Society, 1973
1. In [2,5,6,7] a.o. several interpretations of the inequalityfor allsuch thatwere given and the following was proved.
Aczél, J., Ostrowski, A. M.
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Shannon Entropy Estimation for Linear Processes [PDF]

Journal of Risk and Financial Management, 2020
In this paper, we estimate the Shannon entropy S(f)=−E[log(f(x))] of a one-sided linear process with probability density function f(x). We employ the integral estimator Sn(f), which utilizes the standard kernel density estimator fn(x) of f(x). We show that Sn(f) converges to S(f) almost surely and in Ł2 under reasonable conditions.
Timothy Fortune, Hailin Sang
openaire   +3 more sources

Shannon Entropy Reinterpreted [PDF]

Reports on Mathematical Physics, 2018
In this paper we remark that Shannon entropy can be expressed as a function of the self-information (i.e. the logarithm) and the inverse of the Lambert $W$ function. It means that we consider that Shannon entropy has the trace form: $-k \sum_{i} W^{-1} \circ \mathsf{ln}(p_{i})$.
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Multi-Level Wavelet Shannon Entropy-Based Method for Single-Sensor Fault Location

Entropy, 2015
In actual application, sensors are prone to failure because of harsh environments, battery drain, and sensor aging. Sensor fault location is an important step for follow-up sensor fault detection.
Qiaoning Yang, Jianlin Wang
doaj   +1 more source