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Titlebook: Entropy Measures, Maximum Entropy Principle and Emerging Applications; Karmeshu Book 2003 Springer-Verlag Berlin Heidelberg 2003 Applied I

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Entropy and Complexity of Sequences,ing to their entropies, syntactic-complexity and informational content. Using these measures to classify these sequences with respect to their structure or randomness, give similar results. The other examples show significantly less order.
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978-3-642-05531-7Springer-Verlag Berlin Heidelberg 2003
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Entropy Measures, Maximum Entropy Principle and Emerging Applications978-3-540-36212-8Series ISSN 1434-9922 Series E-ISSN 1860-0808
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Edible Packaging from Legume By-Products,is conceived, in general, within a broad framework consisting of fuzzy set theory and fuzzy measure theory. This framework is sufficiently general to capture virtually all conceivable types of uncertainty via appropriate uncertainty theories. Three levels are distinguished in each uncertainty theory
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,Mit Hypnose Gedächtnis-Updates kreieren,e process is Markovian. From the propagator, the Fokker-Planck equation can be derived. The Lagrange parameters that are used in the maximum information entropy principle can be derived by minimizing the Kullback information.
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Ticiana C. Rodrigues M.D.,Poli Mara Spritzering the entropy of non-random functions. And then, we use the MEP to obtain an estimate of the probability distribution of complex-valued fractional Brownian motion defined as the limit of a random walk on the complex roots of the unity in the complex plane, thus exhibiting a relation between comple
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Update in Pediatric Critical Carestatistical and information-theoretic analysis on a database. Based on the attribute values, a database can be partitioned into smaller populations. An attribute is deemed important if it partitions the database such that previously unknown regularities and patterns are observable. Many information-
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