Hierarchical symbol transition entropy
WebSociology states that entropy is the social decline or natural decay of structure (such as law, organization, and convention) in a social system. In cosmology, entropy is described as a hypothetical tendency of the universe to attain a state of maximum homogeneity. It states that the matter should be at a uniform temperature. Web28 de set. de 2024 · Using this effective thermodynamic framework, we establish a partitioning of the total entropy production into two contributions that individually verify …
Hierarchical symbol transition entropy
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Web1 de abr. de 2024 · The TFI is combined with conditional entropy of ordinal patterns and complexity measure to form a novel three-dimensional graph, called transition-based … WebHierarchical Symbol Transition Entropy: A Novel Feature Extractor for Machinery Health Monitoring Abstract: This article develops a novel collaborative health monitoring framework based on hierarchical symbol transition entropy (HSTE) and 2-D-extreme learning …
Web15 de fev. de 2014 · Hierarchical Symbol Transition Entropy: A Novel Feature Extractor for Machinery Health Monitoring. 2024, IEEE Transactions on Industrial Informatics. On Entropy, Entropy-Like Quantities, and Applications. 2024, Frontiers In Entropy Across The Disciplines - Panorama Of Entropy: Theory, Computation, And Applications. Web5 de out. de 2024 · High-entropy-oxides (HEOs), a new class of solids that contain five or more elemental species, have attracted increasing interests owing to their unique structures and fascinating physicochemical properties. However, it is a huge challenge to construct various nanostructured, especially low-dimensional nanostructured HEOs under the high …
WebSubsequently, a new feature representation method called hierarchical symbol transition entropy is proposed by combining STE with the hierarchical analysis. The two-order tensor features can be constructed for multichannel data by stacking HSTE values extracted from each single-channel data. WebThis article details a two-step method of quantifying eye movement transitions between areas of interest (AOIs). First, individuals' gaze switching patterns, represented by fixated AOI sequences, are modeled as Markov chains. Second, Shannon's entropy ...
WebThis paper develops a novel collaborative health monitoring framework based on hierarchical symbol transition entropy (HSTE) and 2D-extreme learning machine (2D …
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