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hal.structure.identifierTélécom Paris
hal.structure.identifierInstitut Polytechnique de Paris [IP Paris]
dc.contributor.authorDELSOL, Idris
hal.structure.identifierCommunications Numériques [COMNUM]
hal.structure.identifierDépartement Communications & Electronique [COMELEC]
dc.contributor.authorRIOUL, Olivier
hal.structure.identifierCommunications Numériques [COMNUM]
hal.structure.identifierDépartement Communications & Electronique [COMELEC]
dc.contributor.authorBÉGUINOT, Julien
hal.structure.identifierCentre Sciences des Processus Industriels et Naturels [SPIN-ENSMSE]
hal.structure.identifierÉcole des Mines de Saint-Étienne [Mines Saint-Étienne MSE]
hal.structure.identifierLaboratoire Ondes et Matière d'Aquitaine [LOMA]
hal.structure.identifierUniversité de Bordeaux [UB]
dc.contributor.authorRABIET, Victor
hal.structure.identifierLaboratoire Instrumentation Intelligente Distribuée et Embarquée (CEA, LIST) [LIIDE (CEA, LIST)]
dc.contributor.authorSOULOUMIAC, Antoine
dc.date.issued2024-01-19
dc.identifier.issn1099-4300
dc.description.abstractEnA new information theoretic condition is presented for reconstructing a discrete random variable X based on the knowledge of a set of discrete functions of X. The reconstruction condition is derived from Shannon’s 1953 lattice theory with two entropic metrics of Shannon and Rajski. Because such a theoretical material is relatively unknown and appears quite dispersed in different references, we first provide a synthetic description (with complete proofs) of its concepts, such as total, common, and complementary information. The definitions and properties of the two entropic metrics are also fully detailed and shown to be compatible with the lattice structure. A new geometric interpretation of such a lattice structure is then investigated, which leads to a necessary (and sometimes sufficient) condition for reconstructing the discrete random variable X given a set {X1,…,Xn} of elements in the lattice generated by X. Intuitively, the components X1,…,Xn of the original source of information X should not be globally “too far away” from X in the entropic distance in order that X is reconstructable. In other words, these components should not overall have too low of a dependence on X; otherwise, reconstruction is impossible. These geometric considerations constitute a starting point for a possible novel “perfect reconstruction theory”, which needs to be further investigated and improved along these lines. Finally, this condition is illustrated in five specific examples of perfect reconstruction problems: the reconstruction of a symmetric random variable from the knowledge of its sign and absolute value, the reconstruction of a word from a set of linear combinations, the reconstruction of an integer from its prime signature (fundamental theorem of arithmetic) and from its remainders modulo a set of coprime integers (Chinese remainder theorem), and the reconstruction of the sorting permutation of a list from a minimal set of pairwise comparisons.
dc.language.isoen
dc.publisherMDPI
dc.subject.eninformation lattice
dc.subject.encommon information
dc.subject.encomplementary information
dc.subject.enRajski distance
dc.subject.enShannon distance
dc.subject.endependency coefficient
dc.subject.enrelative redundancy
dc.subject.enconvex envelope
dc.subject.enperfect reconstruction
dc.subject.enSignal processing
dc.title.enAn Information Theoretic Condition for Perfect Reconstruction
dc.typeArticle de revue
dc.identifier.doi10.3390/e26010086
dc.subject.halInformatique [cs]/Traitement du signal et de l'image
dc.subject.halMathématiques [math]/Géométrie métrique [math.MG]
bordeaux.journalEntropy
bordeaux.page86
bordeaux.volume26
bordeaux.issue1
bordeaux.peerReviewedoui
hal.identifierhal-04416099
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-04416099v1
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