Search results for "CONST"

showing 10 items of 7706 documents

Probability Propagation in Selected Aristotelian Syllogisms

2019

This paper continues our work on a coherence-based probability semantics for Aristotelian syllogisms (Gilio, Pfeifer, and Sanfilippo, 2016; Pfeifer and Sanfilippo, 2018) by studying Figure III under coherence. We interpret the syllogistic sentence types by suitable conditional probability assessments. Since the probabilistic inference of $P|S$ from the premise set ${P|M, S|M}$ is not informative, we add $p(M|(S ee M))>0$ as a probabilistic constraint (i.e., an ``existential import assumption'') to obtain probabilistic informativeness. We show how to propagate the assigned premise probabilities to the conclusion. Thereby, we give a probabilistic meaning to all syllogisms of Figure~III. We…

Discrete mathematicsSettore MAT/06 - Probabilita' E Statistica Matematica05 social sciencesProbabilistic logicSyllogismConditional probability02 engineering and technologyCoherence (statistics)Settore MAT/01 - Logica MatematicaImprecise probabilityAristotelian syllogismFigure III050105 experimental psychologyConstraint (information theory)Premise0202 electrical engineering electronic engineering information engineeringImprecise probability020201 artificial intelligence & image processing0501 psychology and cognitive sciencesConditional eventDefault reasoningCoherenceSentenceMathematics
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Randomized renaming in shared memory systems.

2021

Abstract Renaming is a task in distributed computing where n processes are assigned new names from a name space of size m . The problem is called tight if m = n , and loose if m > n . In recent years renaming came to the fore again and new algorithms were developed. For tight renaming in asynchronous shared memory systems, Alistarh et al. describe a construction based on the AKS network that assigns all names within O ( log n ) steps per process. They also show that, depending on the size of the name space, loose renaming can be done considerably faster. For m = ( 1 + ϵ ) ⋅ n and constant ϵ , they achieve a step complexity of O ( log log n ) . In this paper we consider tight as well as loos…

Discrete mathematicsShared memory modelSpeedupComputer Networks and CommunicationsComputer science020206 networking & telecommunications02 engineering and technologyParallel computingTheoretical Computer ScienceRandomized algorithmTask (computing)Constant (computer programming)Shared memoryArtificial IntelligenceHardware and ArchitectureAsynchronous communicationDistributed algorithm0202 electrical engineering electronic engineering information engineeringOverhead (computing)020201 artificial intelligence & image processingSoftware
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On approximation of a class of stochastic integrals and interpolation

2004

Given a diffusion Y = (Y_{t})_{t \in [0,T]} we give different equivalent conditions so that a stochastic integral has an L 2-approximation rate of n −η, {\rm \eta \in (0,1/2],} if one approximates by integrals over piece-wise constant integrands where equidistant time nets of cardinality n + 1 are used. In particular, we obtain assertions in terms of smoothness properties of g(Y T ) in the sense of Malliavin calculus. After optimizing over non-equidistant time-nets of cardinality n + 1 in case {\rm \eta > 0} , it turns out that one always obtains a rate of n^{ - 1/2}, which is optimal. This applies to all functions g obtained in an appropriate way by the real interpolation method between th…

Discrete mathematicsSobolev spaceSmoothness (probability theory)CardinalityRate of convergenceEquidistantConstant (mathematics)Malliavin calculusInterpolationMathematicsStochastics and Stochastic Reports
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Impact of common property (E.A.) on fixed point theorems in fuzzy metric spaces

2011

We observe that the notion of common property (E.A.) relaxes the required containment of range of one mapping into the range of other which is utilized to construct the sequence of joint iterates. As a consequence, a multitude of recent fixed point theorems of the existing literature are sharpened and enriched.

Discrete mathematicsT57-57.97QA299.6-433Containment (computer programming)Pure mathematicsSequenceApplied mathematics. Quantitative methodsApplied MathematicsFixed-point theoremConstruct (python library)Fuzzy metric space property (E.A.) common property (E.A.) common fixed point generalized fuzzy contractionRange (mathematics)Differential geometryIterated functionSettore MAT/05 - Analisi MatematicaCommon propertyGeometry and TopologyAnalysisMathematics
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Nondeterministic Moore automata and Brzozowski's minimization algorithm

2012

AbstractMoore automata represent a model that has many applications. In this paper we define a notion of coherent nondeterministic Moore automaton (NMA) and show that such a model has the same computational power of the classical deterministic Moore automaton. We consider also the problem of constructing the minimal deterministic Moore automaton equivalent to a given NMA. We propose an algorithm that is a variant of Brzozowski’s minimization algorithm in the sense that it is essentially structured as reverse operation and subset construction performed twice. Moreover, we explore more general classes of NMA and analyze the applicability of the algorithm. For some of such classes the algorith…

Discrete mathematicsTheoryofComputation_COMPUTATIONBYABSTRACTDEVICESGeneral Computer ScienceBrzozowski’s minimization algorithmSettore INF/01 - InformaticaPowerset constructionAutomata minimizationBüchi automatonNonlinear Sciences::Cellular Automata and Lattice GasesTheoretical Computer ScienceNondeterministic algorithmDeterministic finite automatonTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESDFA minimizationDeterministic automatonTwo-way deterministic finite automatonNondeterministic finite automatonBrzozowski's minimization algorithmComputer Science::Formal Languages and Automata TheoryComputer Science(all)MathematicsNondeterministic Moore automata
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Automata with Extremal Minimality Conditions

2010

It is well known that the minimality of a deterministic finite automaton (DFA) depends on the set of final states. In this paper we study the minimality of a strongly connected DFA by varying the set of final states. We consider, in particular, some extremal cases. A strongly connected DFA is called uniformly minimal if it is minimal, for any choice of the set of final states. It is called never-minimal if it is not minimal, for any choice of the set of final states. We show that there exists an infinite family of uniformly minimal automata and that there exists an infinite family of never-minimal automata. Some properties of these automata are investigated and, in particular, we consider t…

Discrete mathematicsTheoryofComputation_COMPUTATIONBYABSTRACTDEVICESPowerset constructionBüchi automatonω-automatonNonlinear Sciences::Cellular Automata and Lattice GasesCombinatoricsTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESDFA minimizationDeterministic automatonQuantum finite automataTwo-way deterministic finite automatonNondeterministic finite automatonComputer Science::Formal Languages and Automata TheoryAutomata MinimizationMathematics
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Nondeterministic Moore Automata and Brzozowski’s Algorithm

2011

Moore automata represent a model that has many applications. In this paper we define a notion of coherent nondeterministic Moore automaton (NMA) and show that such a model has the same computational power of the classical deterministic Moore automaton. We consider also the problem of constructing the minimal deterministic Moore automaton equivalent to a given NMA. In this paper we propose an algorithm that is a variant of Brzozowski's algorithm in the sense that it is essentially structured as reverse operation and subset construction performed twice.

Discrete mathematicsTheoryofComputation_COMPUTATIONBYABSTRACTDEVICESSettore INF/01 - InformaticaPowerset constructionBüchi automatonNonlinear Sciences::Cellular Automata and Lattice GasesNondeterministic algorithmTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESDeterministic finite automatonDFA minimizationDeterministic automatonTwo-way deterministic finite automatonMoore automata minimization Brzozowski'algorithmNondeterministic finite automatonAlgorithmComputer Science::Formal Languages and Automata TheoryMathematics
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Efficient CNF Encoding of Boolean Cardinality Constraints

2003

In this paper, we address the encoding into CNF clauses of Boolean cardinality constraints that arise in many practical applications. The proposed encoding is efficient with respect to unit propagation, which is implemented in almost all complete CNF satisfiability solvers. We prove the practical efficiency of this encoding on some problems arising in discrete tomography that involve many cardinality constraints. This encoding is also used together with a trivial variable elimination in order to re-encode parity learning benchmarks so that a simple Davis and Putnam procedure can solve them.

Discrete mathematicsTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESCardinalityUnit propagationComputer scienceConstrained optimizationData_CODINGANDINFORMATIONTHEORYVariable eliminationComputer Science::Computational ComplexityConjunctive normal formBoolean data typeSatisfiability
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Fractional wavelet transform

1997

The wavelet transform, which has had a growing importance in signal and image processing, has been generalized by association with both the wavelet transform and the fractional Fourier transform. Possible implementations of the new transformation are in image compression, image transmission, transient signal processing, etc. Computer simulations demonstrate the abilities of the novel transform. Optical implementation of this transform is briefly discussed.

Discrete wavelet transformLifting schemeComputer scienceNon-uniform discrete Fourier transformMaterials Science (miscellaneous)Stationary wavelet transformComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONTop-hat transformImage processingData_CODINGANDINFORMATIONTHEORYIndustrial and Manufacturing EngineeringDiscrete Fourier transformWavelet packet decompositionsymbols.namesakeDiscrete Fourier transform (general)Multidimensional signal processingOpticsWaveletHartley transformBusiness and International ManagementS transformConstant Q transformContinuous wavelet transformSignal processingbusiness.industrySecond-generation wavelet transformFourier opticsShort-time Fourier transformWavelet transformFractional wavelet transformFractional Fourier transformTime–frequency analysisFourier transformsymbolsHarmonic wavelet transformbusinessAlgorithmImage compression
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Two-dimensional wavelet transform by wavelength multiplexing

1996

The wavelet transform is a useful tool for data compression, analysis of short transient pulses, optical correlators, etc. This transform was obtained optically by the use of the spatial or temporal multiplexing approaches. A two-dimensional wavelet transform is obtained with only one spatial channel. The information of the different scalings is carried in different wavelengths and summed incoherently at the output plane. Laboratory experimental results are demonstrated.

Discrete wavelet transformPhysicsbusiness.industryMaterials Science (miscellaneous)Wavelet transformIndustrial and Manufacturing EngineeringWavelet packet decompositionOpticsWaveletBusiness and International ManagementbusinessHarmonic wavelet transformFast wavelet transformContinuous wavelet transformConstant Q transformApplied Optics
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