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Full-Text Articles in Physics
A Super Fast Algorithm For Estimating Sample Entropy, Weifeng Liu, Ying Jiang, Yuesheng Xu
A Super Fast Algorithm For Estimating Sample Entropy, Weifeng Liu, Ying Jiang, Yuesheng Xu
Mathematics & Statistics Faculty Publications
: Sample entropy, an approximation of the Kolmogorov entropy, was proposed to characterize complexity of a time series, which is essentially defined as − log(B/A), where B denotes the number of matched template pairs with length m and A denotes the number of matched template pairs with m + 1, for a predetermined positive integer m. It has been widely used to analyze physiological signals. As computing sample entropy is time consuming, the box-assisted, bucket-assisted, x-sort, assisted sliding box, and kd-tree-based algorithms were proposed to accelerate its computation. These algorithms require O(N2) or …
Extractable Entanglement From A Euclidean Hourglass, Takanori Anegawa, Norihiro Iizuka, Daniel Kabat
Extractable Entanglement From A Euclidean Hourglass, Takanori Anegawa, Norihiro Iizuka, Daniel Kabat
Publications and Research
We previously proposed that entanglement across a planar surface can be obtained from the partition function on a Euclidean hourglass geometry. Here we extend the prescription to spherical entangling surfaces in conformal field theory. We use the prescription to evaluate log terms in the entropy of a conformal field theory in two dimensions, a conformally coupled scalar in four dimensions, and a Maxwell field in four dimensions. For Maxwell we reproduce the extractable entropy obtained by Soni and Trivedi. We take this as evidence that the hourglass prescription provides a Euclidean technique for evaluating extractable entropy in quantum field theory.
Neuronal Correlation Parameter In The Idea Of Thermodynamic Entropy Of An N-Body Gravitationally Bounded System, Ioannis Haranas, Ioannis Gkigkitzis, Ilias S. Kotsireas, Carlos Austerlitz
Neuronal Correlation Parameter In The Idea Of Thermodynamic Entropy Of An N-Body Gravitationally Bounded System, Ioannis Haranas, Ioannis Gkigkitzis, Ilias S. Kotsireas, Carlos Austerlitz
Physics and Computer Science Faculty Publications
Understanding how the brain encodes information and performs computation requires statistical and functional analysis. Given the complexity of the human brain, simple methods that facilitate the interpretation of statistical correlations among different brain regions can be very useful. In this report we introduce a numerical correlation measure that may serve the interpretation of correlational neuronal data, and may assist in the evaluation of different brain states. The description of the dynamical brain system, through a global numerical measure may indicate the presence of an action principle which may facilitate a application of physics principles in the study of the human …
Bekenstein Bound Of Information Number N And Its Relation To Cosmological Parameters In A Universe With And Without Cosmological Constant, Ioannis Haranas, Ioannis Gkigkitzis
Bekenstein Bound Of Information Number N And Its Relation To Cosmological Parameters In A Universe With And Without Cosmological Constant, Ioannis Haranas, Ioannis Gkigkitzis
Physics and Computer Science Faculty Publications
Bekenstein has obtained is an upper limit on the entropy S, and from that, an information number bound N is deduced. In other words, this is the information contained within a given finite region of space that includes a finite amount of energy. Similarly, this can be thought as the maximum amount of information required to perfectly describe a given physical system down to its quantum level. If the energy and the region of space are finite then the number of information N required in describing the physical system is also finite. In this short letter two information number …