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Distinguishing models of growth with approximate entropy
2000Publisher Summary This chapter provides information on the distinguishing models of growth, with approximate entropy. The chapter explains a unique application of approximate entropy, approximate entropy (ApEn) to distinguish the models of growth in children.
M L, Johnson, M, Lampl, M, Straume
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Gaussian Approximation Numbers and Metric Entropy
Journal of Mathematical Sciences, 2019zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kühn, T., Linde, W.
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Approximating the Differential Entropy of Gaussian Mixtures
GLOBECOM 2017 - 2017 IEEE Global Communications Conference, 2017A Gaussian mixture is a weighted sum of several Gaussian densities. The probability density function (PDF) of the output of an additive white Gaussian noise (AWGN) channel with discrete input can be regarded as a Gaussian mixture. By constructing a sequence of functions to approach the Gaussian mixture, this paper presents a new approximation for the ...
Chenchen Zhang, Yuan Luo 0003
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Approximate entropy as indication of goodness-of-fit
2000Publisher Summary This chapter provides information on the approximate entropy, approximate entropy (ApEn), as indication of goodness-of-fit criterion. ApEn is a measure of the regularity or orderliness of a sequence of numbers. It calibrates sequential relationships, between the numbers, in terms of the randomness of the numbers.
M L, Johnson, M, Straume
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Approximate entropy (ApEn) as a complexity measure
Chaos: An Interdisciplinary Journal of Nonlinear Science, 1995Approximate entropy (ApEn) is a recently developed statistic quantifying regularity and complexity, which appears to have potential application to a wide variety of relatively short (greater than 100 points) and noisy time-series data. The development of ApEn was motivated by data length constraints commonly encountered, e.g., in heart rate, EEG, and ...
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Tensor approximate entropy: An entropy measure for sleep scoring
Knowledge-Based Systems, 2022Yuwen Li 0002 +4 more
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Minimum Entropy Light and Shading Approximation
Procedings of the British Machine Vision Conference 2006, 2006An estimation method for approximating the lighting of a multi-view scene is developed. It is assumed that a set of scene patches can be obtained with estimates of their normals and depths from a given camera. The effect of lighting on the scene is modelled as multiplicative and additive bias-fields, represented by spherical harmonic (SH) basis ...
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Correlation dimension and approximate entropy for machine condition monitoring: Revisited
Mechanical Systems and Signal Processing, 2021Dong Wang +2 more
exaly
Approximation and relative entropy
2012We re-visit the notion of Approximate Confinement in terms of information theory. This notion formalises probabilistic non-interference in terms of process indistinguishability. We show that it corresponds to the notion of relative entropy, aka Kullback-Leibler divergence.
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