Titlebook: New Foundations for Information Theory; Logical Entropy and David Ellerman Book 2021 The Author(s), under exclusive license to Springer Na

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Quantum Logical Information Theory,ty matrices. Then the transition to the quantum version of logical entropy is made using the semi-algorithmic procedure of “linearization.” Given a concept applied to sets, apply that concept to the basis set of a vector space and whatever it linearly generates gives the corresponding vector space c

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Logical Entropy,l entropy is first defined in terms of the set of distinctions of a partition and then a probability measure on the set defines the quantitative version of logical entropy. We give a history of the logical entropy formula that goes back to Corrado Gini’s 1912 “index of mutability” and has been rediscovered many times.

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2211-4548 gical entropy approach to the MaxEntropy method.Presents a nThis monograph offers a new foundation for information theory that is based on the notion of information-as-distinctions, being directly measured by logical entropy, and on the re-quantification as Shannon entropy, which is the fundamental

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The Compound Notions for Logical and Shannon Entropies,loped for logical entropy along with the corresponding notions for Shannon entropy. And finally, a number of intriguing parallels between the two entropies and related inequalities are developed which allow some inequalities directly relating the two entropies.

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https://doi.org/10.1007/978-3-030-86552-8entropy; partition logic; information theory; logical entropy; Shannon entropy; logical probability; index