Results 271 to 280 of about 83,436 (308)

Information Meaning of Entropy of Nonergodic Measures

Differential Equations, 2019
The main aim of this paper is to study the limit frequency properties of trajectories of the simplest dynamical system generated by the left shift on the space of sequences of letters from a finite alphabet. More precisely, a modification of the Shannon-McMillan-Breiman theorem is proved: for any invariant (not necessarily ergodic) probability measure \
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Measuring information transfer by dispersion transfer entropy

Communications in Nonlinear Science and Numerical Simulation, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Boyi Zhang, Pengjian Shang
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Information entropy as a measure of DEM quality

Computers & Geosciences, 2012
The Shannon-Weaver Information statistic has been proposed as a useful measure of the quality of a Digital Elevation Model. However the statistic, usually referred to as entropy, is based purely on the range of values in a dataset and their relative proportion and is not directly related to the accuracy of those values or their spatial arrangement ...
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Relative Entropy as a Measure of Diagnostic Information

Medical Decision Making, 1999
Relative entropy is a concept within information theory that provides a measure of the distance between two probability distributions. The author proposes that the amount of information gained by performing a diagnostic test can be quantified by calculating the relative entropy between the posttest and pretest probability distributions. This statistic,
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Information‐theoretical entropy as a measure of sequence variability

Proteins: Structure, Function, and Bioinformatics, 1991
AbstractWe propose the use of the information‐theoretical entropy, S = −Σpi log2 Pi, as a measure of variability at a given position in a set of aligned sequences. pi stands for the fraction of times the i‐th type appears at a position. For protein sequences, the sum has up to 20 terms, for nucleotide sequences, up to 4 terms, and for codon sequences ...
P S, Shenkin, B, Erman, L D, Mastrandrea
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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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Generalizations of Entropy and Information Measures

2015
This paper presents and discusses two generalized forms of the Shannon entropy, as well as a generalized information measure. These measures are applied on a exponential-power generalization of the usual Normal distribution, emerged from a generalized form of the Fisher’s entropy type information measure, essential to Cryptology.
Thomas L. Toulias, Christos P. Kitsos
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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
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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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