Search results for "image processing"

showing 10 items of 3285 documents

Soft ditopological spaces

2015

We introduce the concept of a soft ditopological space as the "soft Generalization" of the concept of a ditopological space as it is defined in the papers by L.M. Brown and co-authors, see e.g. L. M. Brown, R. Ert?rk, ?. Dost, Ditopological texture spaces and fuzzy topology, I. Basic Concepts, Fuzzy Sets and Systems 147 (2) (2004), 171-199. Actually a soft ditopological space is a soft set with two independent structures on it - a soft topology and a soft co-topology. The first one is used to describe openness-type properties of a space while the second one deals with its closedness-type properties. We study basic properties of such spaces and accordingly defined continuous mappings between…

Pure mathematicsGeneralizationGeneral MathematicsFuzzy set010103 numerical & computational mathematics02 engineering and technologySpace (mathematics)01 natural sciencesFuzzy topologyGeneral Mathematics (math.GM)FOS: Mathematics0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processing0101 mathematicsMathematics - General MathematicsTopology (chemistry)MathematicsSoft setFilomat
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A C0-Semigroup of Ulam Unstable Operators

2020

The Ulam stability of the composition of two Ulam stable operators has been investigated by several authors. Composition of operators is a key concept when speaking about C0-semigroups. Examples of C0-semigroups formed with Ulam stable operators are known. In this paper, we construct a C0-semigroup (Rt)t&ge

Pure mathematicsPhysics and Astronomy (miscellaneous)General MathematicsMathematicsofComputing_GENERAL02 engineering and technology01 natural sciencesStability (probability)Domain (mathematical analysis)Chebyshev expansion0103 physical sciencescomposition of operatorsData_FILES0202 electrical engineering electronic engineering information engineeringComputer Science (miscellaneous)Infinitesimal generatorC0-semigroupNonlinear Sciences::Pattern Formation and SolitonsMathematicsMathematics::Functional Analysis010308 nuclear & particles physicsSemigroupMathematics::Operator Algebraslcsh:MathematicsUlam stabilityComposition (combinatorics)lcsh:QA1-939Nonlinear Sciences::Chaotic Dynamics<i>C</i><sub>0</sub>-semigroupsTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESChemistry (miscellaneous)Chebyshev expansion020201 artificial intelligence & image processingSymmetry
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Ulam Stability for the Composition of Operators

2020

Working in the setting of Banach spaces, we give a simpler proof of a result concerning the Ulam stability of the composition of operators. Several applications are provided. Then, we give an example of a discrete semigroup with Ulam unstable members and an example of Ulam stable operators on a Banach space, such that their sum is not Ulam stable. Another example is concerned with a C 0 -semigroup ( T t ) t &ge

Pure mathematicsPhysics and Astronomy (miscellaneous)General MathematicsOpen problemBanach space02 engineering and technology01 natural sciencesStability (probability)closed linear subspacescomposition of operators0202 electrical engineering electronic engineering information engineeringComputer Science (miscellaneous)0101 mathematicsNonlinear Sciences::Pattern Formation and SolitonsMathematicsMathematics::Functional AnalysisSemigrouplcsh:Mathematics010102 general mathematicsUlam stabilityComposition (combinatorics)lcsh:QA1-939Nonlinear Sciences::Chaotic Dynamics<i>C</i><sub>0</sub>-semigroupsTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESChemistry (miscellaneous)Computer Science::Programming Languages020201 artificial intelligence & image processingSymmetry
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Multifunctions determined by integrable functions

2019

Integral properties of multifunctions determined by vector valued functions are presented. Such multifunctions quite often serve as examples and counterexamples. In particular it can be observed that the properties of being integrable in the sense of Bochner, McShane or Birkhoff can be transferred to the generated multifunction while Henstock integrability does not guarantee it.

Pure mathematicsPositive multifunctionIntegrable systemApplied Mathematicsselection02 engineering and technologymultifunction determined by a functionTheoretical Computer ScienceFunctional Analysis (math.FA)28B20 26E25 26A39 28B05 46G10 54C60 54C65Mathematics - Functional AnalysisPositive multifunction gauge integral selection multifunction determined by a function measure theory.measure theorySettore MAT/05 - Analisi MatematicaArtificial Intelligence020204 information systemsgauge integral0202 electrical engineering electronic engineering information engineeringFOS: Mathematics020201 artificial intelligence & image processingVector-valued functionSoftwareCounterexampleMathematics
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Decompositions of Weakly Compact Valued Integrable Multifunctions

2020

We give a short overview on the decomposition property for integrable multifunctions, i.e., when an &ldquo

Pure mathematicsProperty (philosophy)Integrable systemGeneral MathematicsPhysics::Medical PhysicsMathematics::Optimization and ControlBanach space02 engineering and technologyCharacterization (mathematics)Translation (geometry)01 natural sciencesSeparable spaceSettore MAT/05 - Analisi Matematica0202 electrical engineering electronic engineering information engineeringComputer Science (miscellaneous)Decomposition (computer science)0101 mathematicsEngineering (miscellaneous)MathematicsMathematics::Functional Analysislcsh:Mathematics010102 general mathematicsRegular polygonGauge multivalued integrallcsh:QA1-939scalarly defined multivalued integralComputer Science::Otherdecomposition of a multifunction020201 artificial intelligence & image processing
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Algebraic aspects and coherence conditions for conjoined and disjoined conditionals

2019

We deepen the study of conjoined and disjoined conditional events in the setting of coherence. These objects, differently from other approaches, are defined in the framework of conditional random quantities. We show that some well known properties, valid in the case of unconditional events, still hold in our approach to logical operations among conditional events. In particular we prove a decomposition formula and a related additive property. Then, we introduce the set of conditional constituents generated by $n$ conditional events and we show that they satisfy the basic properties valid in the case of unconditional events. We obtain a generalized inclusion-exclusion formula and we prove a …

Pure mathematicsProperty (philosophy)Settore MAT/06 - Probabilita' E Statistica MatematicaDistributivityApplied MathematicsProbability (math.PR)02 engineering and technologyCoherence (statistics)Characterization (mathematics)Settore MAT/01 - Logica Matematica60Axx 03B48Theoretical Computer ScienceCoherenceConditional random quantities Conjunction and disjunction of conditionals Decomposition formula Conditional constituents Inclusion-exclusion formulaSet (abstract data type)Artificial Intelligence020204 information systemsFOS: Mathematics0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingInclusion–exclusion principleAlgebraic numberMathematics - ProbabilitySoftwareCounterexampleMathematics
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Biorthogonal Wavelet Transforms Originating from Discrete and Discrete-Time Splines

2018

This chapter describes how to generate families of biorthogonal wavelet transforms in spaces of periodic signals using prediction p-filters originating from discrete-time and discrete splines. The transforms are generated by the lifting scheme (Sweldens (Wavelet applications in signal and image processing III, vol 2569, 1995, [7]), Sweldens (Appl Comput Harmon Anal 3:186–200, 1996, [8]), Sweldens (SIAM J Math Anal 29:511–546, 1997, [9]), see also Sect. 7.1 of this volume). The discrete-time wavelets related to those transforms are (anti)symmetric, well localized in time domain and have flat spectra. These families comprise wavelets with any number of local discrete vanishing moments (LDVMs)…

Pure mathematicsWaveletLifting schemeDiscrete time and continuous timeFast Fourier transformImage processingFilter (signal processing)Time domainBiorthogonal waveletMathematics
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Hierarchical Syntactic Models for Human Activity Recognition through Mobility Traces

2019

AbstractRecognizing users’ daily life activities without disrupting their lifestyle is a key functionality to enable a broad variety of advanced services for a Smart City, from energy-efficient management of urban spaces to mobility optimization. In this paper, we propose a novel method for human activity recognition from a collection of outdoor mobility traces acquired through wearable devices. Our method exploits the regularities naturally present in human mobility patterns to construct syntactic models in the form of finite state automata, thanks to an approach known asgrammatical inference. We also introduce a measure ofsimilaritythat accounts for the intrinsic hierarchical nature of su…

QA75Computer science02 engineering and technologyManagement Science and Operations ResearchSimilarity measureMachine learningcomputer.software_genreZA4050Set (abstract data type)Activity recognitionGrammatical inference Human activity recognition Mobility020204 information systemsSmart citySimilarity (psychology)0202 electrical engineering electronic engineering information engineeringSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniFinite-state machineT1business.industryGrammar inductionComputer Science ApplicationsHardware and Architecture020201 artificial intelligence & image processingArtificial intelligenceGranularitybusinesscomputer
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A Context-Aware System for Ambient Assisted Living

2017

In the near future, the world's population will be characterized by an increasing average age, and consequently, the number of people requiring for a special household assistance will dramatically rise. In this scenario, smart homes will significantly help users to increase their quality of life, while maintaining a great level of autonomy. This paper presents a system for Ambient Assisted Living (AAL) capable of understanding context and user's behavior by exploiting data gathered by a pervasive sensor network. The knowledge inferred by adopting a Bayesian knowledge extraction approach is exploited to disambiguate the collected observations, making the AAL system able to detect and predict…

QA75Computer sciencemedia_common.quotation_subjectPopulationAmbient Assisted LivingContext (language use)02 engineering and technologyTheoretical Computer ScienceDynamic Bayesian NetworkKnowledge extractionQuality of lifeRule-based reasoningHuman–computer interactionHome automation0202 electrical engineering electronic engineering information engineeringContext awarenesseducationmedia_commonSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionieducation.field_of_studyMulti-sensor data fusionbusiness.industryComputer Science (all)Context awarene020206 networking & telecommunicationsRule-based system020201 artificial intelligence & image processingbusinessWireless sensor networkAutonomy
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An Ambient Intelligence System for Assisted Living

2017

Nowadays, the population's average age is constantly increasing, and thus the need for specialized home assistance is on the rise. Smart homes especially tailored to meet elderly and disabled people's needs can help them maintaining their autonomy, whilst ensuring their safety and well-being. This paper proposes a complete context-aware system for Ambient Assisted Living (AAL), which infers user's actions and context, analyzing its past and current behavior to detect anomalies and prevent possible emergencies. The proposed system exploits Dynamic Bayesian Networks to merge raw data coming from heterogeneous sensors and infer user's behavior and health conditions. A rule-based reasoner is ab…

QA75ExploitComputer sciencemedia_common.quotation_subjectPopulationAmbient Assisted Living02 engineering and technologyAmbient Assisted Living; Multi-sensor data fusion; Dynamic Bayesian Networks; Context awareness; Rule-based ReasoningDynamic Bayesian NetworkHome automationHuman–computer interaction0202 electrical engineering electronic engineering information engineeringeducationDynamic Bayesian networkmedia_commonSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionieducation.field_of_studyAmbient intelligenceMulti-sensor data fusionbusiness.industryRule-based ReasoningContext awarene020206 networking & telecommunicationsSemantic reasoner020201 artificial intelligence & image processingbusinessRaw dataAutonomy
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