Search results for "Iterated function"

showing 10 items of 62 documents

Classification based on Iterative Object Symmetry Transform

2004

The paper shows an application of a new operator named the iterated object transform (IOT) for cell classification. The IOT has the ability to grasp the internal structure of a digital object and this feature can be usefully applied to discriminate structured images. This is the case of cells representing chondrocytes in bone tissue, giarda protozoan, and myeloid leukaemia. A tree classifier allows us to discriminate the three classes with a good accuracy.

Contextual image classificationSettore INF/01 - Informaticabusiness.industryIterative methodFeature extractionGRASPCognitive neuroscience of visual object recognitionPattern recognitionIterated functionComputer visionArtificial intelligencebusinessClassifier (UML)Classification Medical imaging clusteringMathematicsDigital object
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Resonance between Cantor sets

2007

Let $C_a$ be the central Cantor set obtained by removing a central interval of length $1-2a$ from the unit interval, and continuing this process inductively on each of the remaining two intervals. We prove that if $\log b/\log a$ is irrational, then \[ \dim(C_a+C_b) = \min(\dim(C_a) + \dim(C_b),1), \] where $\dim$ is Hausdorff dimension. More generally, given two self-similar sets $K,K'$ in $\RR$ and a scaling parameter $s>0$, if the dimension of the arithmetic sum $K+sK'$ is strictly smaller than $\dim(K)+\dim(K') \le 1$ (``geometric resonance''), then there exists $r<1$ such that all contraction ratios of the similitudes defining $K$ and $K'$ are powers of $r$ (``algebraic resonance…

Discrete mathematicsApplied MathematicsGeneral Mathematics010102 general mathematicsDynamical Systems (math.DS)01 natural sciences010305 fluids & plasmasIrrational rotationCantor setIterated function systemMathematics - Classical Analysis and ODEs28A80 28A78Irrational numberHausdorff dimension0103 physical sciencesArithmetic progressionClassical Analysis and ODEs (math.CA)FOS: MathematicsMathematics - Dynamical Systems0101 mathematicsAlgebraic numberScalingMathematics
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Set-Valued Generalizations of Baire′s Category Theorem

1995

Abstract We prove some generalizations of Baire′s category theorem for chains of iterates of multifunctions defined on Cech-complete spaces. In particular, we extend Lennard′s results stated for functions on complete metric spaces.

Discrete mathematicsApplied MathematicsMathematics::General TopologyBaire spaceBaire measureComplete metric spaceS categoryMetric spaceIterated functionMathematics::Category TheoryBaire category theoremOpen mapping theorem (functional analysis)AnalysisMathematicsJournal of Mathematical Analysis and Applications
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Dimensions of random affine code tree fractals

2014

We calculate the almost sure Hausdorff dimension for a general class of random affine planar code tree fractals. The set of probability measures describing the randomness includes natural measures in random $V$-variable and homogeneous Markov constructions.

Discrete mathematicsCode (set theory)v-variable fractalsApplied MathematicsGeneral MathematicsProbability (math.PR)ta111Dynamical Systems (math.DS)self-similar setsTree (descriptive set theory)Box countingFractalIterated function systemMathematics - Classical Analysis and ODEsHausdorff dimensionClassical Analysis and ODEs (math.CA)FOS: MathematicsAffine transformationMathematics - Dynamical Systems28A80 60D05 37H99RandomnessMathematics - ProbabilityMathematics
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Generalized iterated function systems on the spacel∞(X)

2014

Abstract In the last decades there has been a current effort to extend the classical Hutchinson theory of iterated function systems composed by contractions on a metric space X into itself to more general spaces and infinitely many mappings. In this paper we consider the (countable) iterated function systems consisting of some generalized contractions on the product space X I into X , where I is an arbitrary set of natural numbers. Some approximations of the attractors of the respective iterated function systems are given.

Discrete mathematicsHutchinson operatorMetric spaceIterated function systemCollage theoremApplied MathematicsCountable setContraction mappingTopological conjugacySpace (mathematics)AnalysisMathematicsJournal of Mathematical Analysis and Applications
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The fractal interpolation for countable systems of data

2003

In this paper we will extend the fractal interpolation from the finite case to the case of countable sets of data. The main result is that, given an countable system of data in [a, b] ? Y, where [a, b] is a real interval and Y a compact and arcwise connected metric space, there exists a countable iterated function system whose attractor is the graph of a fractal interpolation function.

Discrete mathematicsMetric spaceFractalIterated function systemGeneral MathematicsAttractorMathematics::General TopologyCountable setSecond-countable spaceCosmic spaceInterpolationMathematicsPublikacije Elektrotehnickog fakulteta - serija: matematika
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Probabilistic entailment and iterated conditionals

2020

In this paper we exploit the notions of conjoined and iterated conditionals, which are defined in the setting of coherence by means of suitable conditional random quantities with values in the interval $[0,1]$. We examine the iterated conditional $(B|K)|(A|H)$, by showing that $A|H$ p-entails $B|K$ if and only if $(B|K)|(A|H) = 1$. Then, we show that a p-consistent family $\mathcal{F}=\{E_1|H_1,E_2|H_2\}$ p-entails a conditional event $E_3|H_3$ if and only if $E_3|H_3=1$, or $(E_3|H_3)|QC(\mathcal{S})=1$ for some nonempty subset $\mathcal{S}$ of $\mathcal{F}$, where $QC(\mathcal{S})$ is the quasi conjunction of the conditional events in $\mathcal{S}$. Then, we examine the inference rules $A…

Discrete mathematicsSettore MAT/06 - Probabilita' E Statistica MatematicaIterated functionInterval (graph theory)Settore MAT/01 - Logica MatematicaCoherence Conditional random quantities p-entailment Inference rules.MathematicsStrict conditional
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Conditional Random Quantities and Compounds of Conditionals

2013

In this paper we consider finite conditional random quantities and conditional previsions assessments in the setting of coherence. We use a suitable representation for conditional random quantities; in particular the indicator of a conditional event $E|H$ is looked at as a three-valued quantity with values 1, or 0, or $p$, where $p$ is the probability of $E|H$. We introduce a notion of iterated conditional random quantity of the form $(X|H)|K$ defined as a suitable conditional random quantity, which coincides with $X|HK$ when $H \subseteq K$. Based on a recent paper by S. Kaufmann, we introduce a notion of conjunction of two conditional events and then we analyze it in the setting of cohere…

Discrete mathematicsSettore MAT/06 - Probabilita' E Statistica MatematicaLogicImport–Export principleProbability (math.PR)Probabilistic logicConjunctionOf the formSettore M-FIL/02 - Logica E Filosofia Della ScienzaCoherence (philosophical gambling strategy)Conditional random quantitieConjunction (grammar)Lower/upper prevision boundsHistory and Philosophy of ScienceNegationIterated functionIterated conditioningFOS: MathematicsConditional eventRepresentation (mathematics)CoherenceDisjunctionMathematics - ProbabilityMathematicsEvent (probability theory)
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Generalized probabilistic modus ponens

2017

Modus ponens (from A and “if A then C” infer C) is one of the most basic inference rules. The probabilistic modus ponens allows for managing uncertainty by transmitting assigned uncertainties from the premises to the conclusion (i.e., from P(A) and P(C|A) infer P(C)). In this paper, we generalize the probabilistic modus ponens by replacing A by the conditional event A|H. The resulting inference rule involves iterated conditionals (formalized by conditional random quantities) and propagates previsions from the premises to the conclusion. Interestingly, the propagation rules for the lower and the upper bounds on the conclusion of the generalized probabilistic modus ponens coincide with the re…

Discrete mathematicsSettore MAT/06 - Probabilita' E Statistica MatematicaProbabilistic logicConjoined conditionalPrevision0102 computer and information sciences02 engineering and technologyCoherence (philosophical gambling strategy)Settore MAT/01 - Logica MatematicaModus ponen01 natural sciencesConditional random quantitieTheoretical Computer ScienceModus ponendo tollens010201 computation theory & mathematicsIterated functionComputer Science0202 electrical engineering electronic engineering information engineeringIterated conditional020201 artificial intelligence & image processingRule of inferenceModus ponensCoherenceEvent (probability theory)Mathematics
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Conditional Random Quantities and Iterated Conditioning in the Setting of Coherence

2013

We consider conditional random quantities (c.r.q.’s) in the setting of coherence. Given a numerical r.q. X and a non impossible event H, based on betting scheme we represent the c.r.q. X|H as the unconditional r.q. XH + μH c , where μ is the prevision assessed for X|H. We develop some elements for an algebra of c.r.q.’s, by giving a condition under which two c.r.q.’s X|H and Y|K coincide. We show that X|HK coincides with a suitable c.r.q. Y|K and we apply this representation to Bayesian updating of probabilities, by also deepening some aspects of Bayes’ formula. Then, we introduce a notion of iterated c.r.q. (X|H)|K, by analyzing its relationship with X|HK. Our notion of iterated conditiona…

Discrete mathematicsSettore MAT/06 - Probabilita' E Statistica MatematicaSettore INF/01 - Informaticaconditional random quantitiesCoherence (statistics)Bayesian inferencebayesian updatingcoherenceCombinatoricsconditional previsionsBayes' theoremIterated functionbayesian updating; conditional random quantities; betting scheme; conditional previsions; coherence; iterated conditioning; iterated conditioning.Coherence betting scheme conditional random quantities conditional previsions Bayesian updating iterated conditioning.Scheme (mathematics)iterated conditioningConditioningRepresentation (mathematics)betting schemeEvent (probability theory)Mathematics
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