Results 261 to 270 of about 176,073,457 (290)

Cumulative Residual Entropy: A New Measure of Information

IEEE Transactions on Information Theory, 2004
In this paper, we use the cumulative distribution of a random variable to define its information content and thereby develop an alternative measure of uncertainty that extends Shannon entropy to random variables with continuous distributions. We call this measure cumulative residual entropy (CRE).
Murali Rao, Yunmei Chen, Baba C. Vemuri, Fei Wang 0002   +3 more
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Identification of entropy as an information measure

2005
Abstract In this chapter, we will use coding theory to prove that the entropy does indeed represent the information content of a set of messages generated according to a set of prescribed probabilities. We will first do this by showing that the average number of bits used per message is equal to the entropy H , if we use the optimal code
A C C Coolen, R Kühn, P Sollich
openaire   +1 more source

Entropy measures and granularity measures for set-valued information systems

Information Sciences, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jianhua Dai, Haowei Tian
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Measurement of the axial displacement with information entropy

Journal of Optics A: Pure and Applied Optics, 2004
For completely describing the movement of a bead in an optical tweezer system, the measurement of the axial movement of the bead is necessary as well as its lateral movement. In order to find a convenient method to measure the axial displacement of the trapped bead, a new method based on Shannon's information entropy is developed. When the bead is in a
J H Bao, Y M Li, L R Lou, Z Wang
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Information and Entropy Measurements on Video Sequences

2005 5th International Conference on Information Communications & Signal Processing, 2006
Video compression techniques usually involve lossy compression algorithms, with much of the original image data being discarded because it is not essential for human perception. However, lossy compression not only reduces data volume substantially, it also removes a reference for how well the remaining data has been compressed. Entropy measurements can
K. Kawaharada, K. Ohzeki, U. Speidel
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Measuring Informativeness of Data by Entropy and Variance

1999
Measuring informativeness of data or news is particularly important as it quantifies the amount of “learning”. This is central to scientific progress as well as to assessing the direction and value of “information” and technologies. As is the case with all “indices”, the desirability of any measure of information depends on at least two considerations:
Nader Ebrahimi, Esfandiar Maasoumi, Ehsan S. Soofi   +2 more
openaire   +1 more source

Measuring cosmic inhomogeneities with information entropy

AIP Conference Proceedings, 2013
In standard cosmology, the global dynamics of the universe is assumed to be described by a homogeneous and isotropic FLRW universe model, but a realistic universe model should include local inhomogeneities, and the physical properties of such a realistic model averaged over a sufficiently large scale do not necessarily coincide with those of the FLRW ...
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Information Measurement and Entropy in Information-Knowledge Certainty

2019
This chapter is devoted to discussions on techniques and methods of information measurement relative to entropy in information-knowledge certainty within the conditions of the system of source-destination dualities. It follows the discussion in Chap.
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Information and entropy of countable measurable partitions. I

Kybernetika, 1974
Summary: This paper proposes a general definition of information function by axiomatic conditions: (a\(_1\)) \(F\) is a continuous function of \(p\in (0,1]\). (a\(_2\)) \(F(\tfrac 12)=F(1), F(1)=0\). (a\(_3\)) \(F(pq)=\varphi(F(p),F(q))\) where \(\varphi\) is a polynomial of its arguments.
Minaketan Behara, Prem Nath
openaire   +2 more sources

Global Sensitivity Analysis Based on Entropy: From Differential Entropy to Alternative Measures

Entropy, 2021
Zdenek Kala
exaly