Normalized compression distance to measure cortico-muscular synchronization [PDF]
Frontiers in Neuroscience, 2022 The neuronal functional connectivity is a complex and non-stationary phenomenon creating dynamic networks synchronization determining the brain states and needed to produce tasks.
Annalisa Pascarella +22 more
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Normalized Compression Distance of Multisets with Applications [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015 Normalized compression distance (NCD) is a parameter-free, feature-free, alignment-free, similarity measure between a pair of finite objects based on compression. However, it is not sufficient for all applications.
Paul Vitanyi, Andrew R Cohen
exaly +6 more sources
Functional balance at rest of hemispheric homologs assessed via normalized compression distance [PDF]
Frontiers in Neuroscience, 2023 IntroductionThe formation and functioning of neural networks hinge critically on the balance between structurally homologous areas in the hemispheres. This balance, reflecting their physiological relationship, is fundamental for learning processes.
Annalisa Pascarella +12 more
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Normalized compression distance for DNA classification [PDF]
PeerJAnalyzing the origin and diversity of numerous genomic sequences, such as those sampled from the human microbiome, is an important first step in genomic analysis. The use of normalized compression distance (NCD) has demonstrated capabilities in the field
Gavin Hearne +4 more
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The Physics, Information, and Computation of Perennial Learning: Kolmogorov Complexity, Information Distance, and Port-Hamiltonian Thermodynamics [PDF]
EntropyReal-world autonomous agents learn under nonstationarity, safety constraints, and finite energetic budgets. We develop a framework for perennial learning—agents that continuously refine their models while provably controlling the cost of forgetting—by ...
Chandrajit Bajaj
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On the Use of Normalized Compression Distances for Image Similarity Detection
Entropy, 2018 This paper investigates the usefulness of the normalized compression distance (NCD) for image similarity detection. Instead of the direct NCD between images, the paper considers the correlation between NCD based feature vectors extracted for each image ...
Dinu Coltuc, Mihai Datcu, Daniela Coltuc
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Semantic Algorithmic Information Theory: From Kolmogorov Complexity to Semantic Equivalence [PDF]
EntropyClassical Algorithmic Information Theory (AIT) provides a rigorous foundation for information-based similarity measurement, but classical formulations and their compression-based approximations largely operate at the syntactic level, making them ...
Jiatong Wu +4 more
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Clustering the Normalized Compression Distance for Influenza Virus Data [PDF]
Lecture Notes in Computer Science, 2010 Kimihito Ito
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Sensors, 2023 The normalized compression distance (NCD) is a similarity measure between a pair of finite objects based on compression. Clustering methods usually use distances (e.g., Euclidean distance, Manhattan distance) to measure the similarity between objects ...
Diogo Azevedo +4 more
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Toward a Simulation Model Complexity Measure
Information, 2023 Is it possible to develop a meaningful measure for the complexity of a simulation model? Algorithmic information theory provides concepts that have been applied in other areas of research for the practical measurement of object complexity.
J. Scott Thompson +4 more
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