Search results for " function"

showing 10 items of 9395 documents

Some Generalizations of a Simion Schmidt Bijection

2007

In 1985, Simion and Schmidt gave a constructive bijection φ from the set of all length (n-1) binary strings having no two consecutive 1s to the set of all length n permutations avoiding all patterns in {123,132,213}. In this paper, we generalize φ to an injective function from {0,1}n-1 to the set Sn of all length n permutations and derive from it four bijections φ : P →Q where P⊆{0,1}n-1 and Q ⊂ Sn. The domains are sets of restricted binary strings and the codomains are sets of pattern-avoiding permutations. As a particular case we retrieve the original Simion–Schmidt bijection. We also show that the bijections obtained are actually combinatorial isomorphisms, i.e. closeness-preserving bije…

Set (abstract data type)Discrete mathematicsGray codeCombinatoricsMathematics::CombinatoricsGeneral Computer ScienceCodomainBijectionIsomorphismBijection injection and surjectionConstructiveInjective functionMathematicsThe Computer Journal
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Closedness Properties in EX-Identification of Recursive Functions

1998

In this paper we investigate in which cases unions of identifiable classes of recursive functions are also necessarily identifiable. We consider identification in the limit with bounds on mindchanges and anomalies. Though not closed under the set union, these identification types still have features resembling closedness. For each of them we find such n that 1) if every union of n - 1 classes out of U1;, . . ., Un is identifiable, so is the union of all n classes; 2) there are such classes U1;, . . ., Un-1 that every union of n-2 classes out of them is identifiable, while the union of n - 1 classes is not. We show that by finding these n we can distinguish which requirements put on the iden…

Set (abstract data type)Discrete mathematicsIdentification (information)Limit (category theory)AlgorithmicsInferenceIdentifiabilityInductive reasoningBoolean functionMathematics
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On the number of factors of Sturmian words

1991

Abstract We prove that for m ⩾1, card( A m ) = 1+∑ m i =1 ( m − i +1) ϕ ( i ) where A m is the set of factors of length m of all the Sturmian words and ϕ is the Euler function. This result was conjectured by Dulucq and Gouyou-Beauchamps (1987) who proved that this result implies that the language (∪ m ⩾0 A m ) c is inherently ambiguous. We also give a combinatorial version of the Riemann hypothesis.

Set (abstract data type)Euler functionCombinatoricssymbols.namesakeRiemann hypothesisGeneral Computer ScienceSturmian wordsymbolsComputer Science(all)Theoretical Computer ScienceMathematicsTheoretical Computer Science
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Stochastic frontier models using R

2020

Abstract The production function is usually assumed to specify the maximum output obtainable, from a given set of inputs, describing the boundary or frontier of the obtainable output from each feasible combination of input; it relates the production process of individual units to the efficient border of the production possibilities. The measure of the distance of each unit from the border is the most immediate way to assess its (in)efficiency. However, the production function is not generally known, but it has only a set of information on each production unit and it is therefore essential to develop techniques to estimate the production frontier. Starting from the packages already developed…

Set (abstract data type)FrontierMathematical optimizationStochastic frontier analysisComputer scienceBoundary (topology)Production (economics)Production functionProduction–possibility frontierMeasure (mathematics)
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A Hierarchy of Twofold Resource Allocation Automata Supporting Optimal Sampling

2009

We consider the problem of allocating limited sampling resources in a "real-time" manner with the purpose of estimating multiple binomial proportions. More specifically, the user is presented with `n ' sets of data points, S 1 , S 2 , ..., S n , where the set S i has N i points drawn from two classes {*** 1 , *** 2 }. A random sample in set S i belongs to *** 1 with probability u i and to *** 2 with probability 1 *** u i , with {u i }. i = 1, 2, ...n , being the quantities to be learnt. The problem is both interesting and non-trivial because while both n and each N i are large, the number of samples that can be drawn is bounded by a constant, c . We solve the problem by first modelling it a…

Set (abstract data type)Mathematical optimizationAsymptotically optimal algorithmHierarchy (mathematics)Learning automataComputer scienceBounded functionContinuous knapsack problemResource allocationStochastic optimization
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Regular k-Surfaces

2012

Roughly speaking, a regular surface in \(\mathbb{R}^3\) is a two-dimensional set of points, in the sense that it can be locally described by two parameters (the local coordinates) and with the property that it is smooth enough (that is, there are no vertices, edges, or self-intersections) to guarantee the existence of a tangent plane to the surface at each point.

Set (abstract data type)PhysicsSurface (mathematics)CombinatoricsLocal coordinatesTangent spacePoint (geometry)Tangent vectorSense (electronics)Implicit function theorem
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A Note on the Density of Rational Functions in A ∞(Ω)

2018

We present a sufficient condition to ensure the density of the set of rational functions with prescribed poles in the algebra A ∞ (Ω).

Set (abstract data type)Pure mathematicsPadé approximantRational functionAlgebra over a fieldMathematics
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Two-Sided Estimates of the Solution Set for the Reaction–Diffusion Problem with Uncertain Data

2009

We consider linear reaction–diffusion problems with mixed Dirichlet–Neumann–Robin conditions. The diffusion matrix, reaction coefficient, and the coefficient in the Robin boundary condition are defined with an uncertainty which allow bounded variations around some given mean values. A solution to such a problem cannot be exactly determined (it is a function in the set of “possible solutions” formed by generalized solutions related to possible data). The problem is to find parameters of this set. In this paper, we show that computable lower and upper bounds of the diameter (or radius) of the set can be expressed throughout problem data and parameters that regulate the indeterminacy range. Ou…

Set (abstract data type)Range (mathematics)Uncertain dataBounded functionMathematical analysisReaction–diffusion systemSolution setFunction (mathematics)Robin boundary conditionMathematics
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A Novel Multidimensional Scaling Technique for Mapping Word-Of-Mouth Discussions

2009

The techniques which utilize Multidimensional Scaling (MDS) as a fundamental statistical tool have been well developed since the late 1970’s. In this paper we show how anMDS scheme can be enhanced by incorporating into it a Stochastic Point Location (SPL) strategy (one which optimizes the former’s gradient descent learning phase) and a new Stress function. The enhanced method, referred to as MDS SPL, has been used in conjunction with a combination of the TF-IDF and Cosine Similarities on a very noisy Word-Of-Mouth (WoM) discussion set consisting of postings concerning mobile phones, yielding extremely satisfying results.

Set (abstract data type)Theoretical computer scienceComputer scienceMobile phoneCosine similarityTrigonometric functionsPoint locationFunction (mathematics)Multidimensional scalingGradient descentAlgorithm
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PARAMETER BOUNDED ESTIMATION FOR QUASISPECIES MODELS OF MOLECULAR EVOLUTION

2006

Abstract The Quasispecies models identification for Evolutionary Dynamics is considered in a worst-case deterministic setting. These models analyze the DNA and RNA evolution or describe the population dynamics of viruses and bacteria. In this paper we identify the Fitness and the Replication Probability parameters of a genetic sequences, subject to a set of stringent constraints to have physical meaning and to guarantee positiveness. The conditional central estimate and the Uncertainty Intervals are determined. The effectiveness of the proposed procedure has been illustrated by means of simulation experiments while tests on real data are under concern.

Set (abstract data type)education.field_of_studyMathematical optimizationIdentification (information)Molecular evolutionBounded functionPopulationReplication (statistics)Viral quasispeciesBiologyeducationEvolutionary dynamicsIFAC Proceedings Volumes
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