Search results for "FOS: Mathematics"

showing 10 items of 1448 documents

Multispectral image denoising with optimized vector non-local mean filter

2016

Nowadays, many applications rely on images of high quality to ensure good performance in conducting their tasks. However, noise goes against this objective as it is an unavoidable issue in most applications. Therefore, it is essential to develop techniques to attenuate the impact of noise, while maintaining the integrity of relevant information in images. We propose in this work to extend the application of the Non-Local Means filter (NLM) to the vector case and apply it for denoising multispectral images. The objective is to benefit from the additional information brought by multispectral imaging systems. The NLM filter exploits the redundancy of information in an image to remove noise. A …

FOS: Computer and information sciencesMulti-spectral imaging systemsComputer Vision and Pattern Recognition (cs.CV)Optimization frameworkMultispectral imageComputer Science - Computer Vision and Pattern Recognition02 engineering and technologyWhite noisePixels[SPI]Engineering Sciences [physics][ SPI ] Engineering Sciences [physics]0202 electrical engineering electronic engineering information engineeringComputer visionUnbiased risk estimatorMultispectral imageMathematicsMultispectral imagesApplied MathematicsBilateral FilterNumerical Analysis (math.NA)Non-local meansAdditive White Gaussian noiseStein's unbiased risk estimatorIlluminationComputational Theory and MathematicsRestorationImage denoisingsymbols020201 artificial intelligence & image processingNon-local mean filtersComputer Vision and Pattern RecognitionStatistics Probability and UncertaintyGaussian noise (electronic)Non- local means filtersAlgorithmsNoise reductionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONFace Recognitionsymbols.namesakeNoise RemovalArtificial IntelligenceFOS: MathematicsParameter estimationMedian filterMathematics - Numerical AnalysisElectrical and Electronic EngineeringFusionPixelbusiness.industryVector non-local mean filter020206 networking & telecommunicationsPattern recognitionFilter (signal processing)Bandpass filters[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsStein's unbiased risk estimators (SURE)NoiseAdditive white Gaussian noiseComputer Science::Computer Vision and Pattern RecognitionSignal ProcessingArtificial intelligenceReconstructionbusinessModel
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Pattern statistics in faro words and permutations

2021

We study the distribution and the popularity of some patterns in $k$-ary faro words, i.e. words over the alphabet $\{1, 2, \ldots, k\}$ obtained by interlacing the letters of two nondecreasing words of lengths differing by at most one. We present a bijection between these words and dispersed Dyck paths (i.e. Motzkin paths with all level steps on the $x$-axis) with a given number of peaks. We show how the bijection maps statistics of consecutive patterns of faro words into linear combinations of other pattern statistics on paths. Then, we deduce enumerative results by providing multivariate generating functions for the distribution and the popularity of patterns of length at most three. Fina…

FOS: Computer and information sciencesMultivariate statisticsDistribution (number theory)Discrete Mathematics (cs.DM)Interlacing0102 computer and information sciences02 engineering and technology[INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM]01 natural sciencesTheoretical Computer ScienceCombinatoricsStatistics[MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO]05A05 (Primary) 05A15 05A19 68R15 (Secondary)0202 electrical engineering electronic engineering information engineeringFOS: MathematicsDiscrete Mathematics and CombinatoricsMathematics - CombinatoricsLinear combinationMathematicsDiscrete mathematicsMathematics::Combinatorics020206 networking & telecommunicationsComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)Derangement010201 computation theory & mathematicsBijectionCombinatorics (math.CO)AlphabetComputer Science::Formal Languages and Automata TheoryComputer Science - Discrete Mathematics
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Fine-tuning the Ant Colony System algorithm through Particle Swarm Optimization

2018

Ant Colony System (ACS) is a distributed (agent- based) algorithm which has been widely studied on the Symmetric Travelling Salesman Problem (TSP). The optimum parameters for this algorithm have to be found by trial and error. We use a Particle Swarm Optimization algorithm (PSO) to optimize the ACS parameters working in a designed subset of TSP instances. First goal is to perform the hybrid PSO-ACS algorithm on a single instance to find the optimum parameters and optimum solutions for the instance. Second goal is to analyze those sets of optimum parameters, in relation to instance characteristics. Computational results have shown good quality solutions for single instances though with high …

FOS: Computer and information sciencesOptimization and Control (math.OC)MathematicsofComputing_NUMERICALANALYSISFOS: MathematicsComputer Science - Neural and Evolutionary ComputingNeural and Evolutionary Computing (cs.NE)Mathematics - Optimization and ControlComputingMethodologies_ARTIFICIALINTELLIGENCE
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On the family of $r$-regular graphs with Grundy number $r+1$

2014

International audience; The Grundy number of a graph $G$, denoted by $\Gamma(G)$, is the largest $k$ such that there exists a partition of $V(G)$, into $k$ independent sets $V_1,\ldots, V_k$ and every vertex of $V_i$ is adjacent to at least one vertex in $V_j$, for every $j < i$. The objects which are studied in this article are families of $r$-regular graphs such that $\Gamma(G) = r + 1$. Using the notion of independent module, a characterization of this family is given for $r=3$. Moreover, we determine classes of graphs in this family, in particular the class of $r$-regular graphs without induced $C_4$, for $r \le 4$. Furthermore, our propositions imply results on partial Grundy number.

FOS: Computer and information sciencesPartial Grundy numberDiscrete Mathematics (cs.DM)Regular graphFalse twinsFOS: MathematicsGrundy numberMathematics - Combinatorics[ INFO.INFO-DM ] Computer Science [cs]/Discrete Mathematics [cs.DM]Combinatorics (math.CO)[INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM]Computer Science - Discrete Mathematics
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Whom to befriend to influence people

2020

Alice wants to join a new social network, and influence its members to adopt a new product or idea. Each person $v$ in the network has a certain threshold $t(v)$ for {\em activation}, i.e adoption of the product or idea. If $v$ has at least $t(v)$ activated neighbors, then $v$ will also become activated. If Alice wants to activate the entire social network, whom should she befriend? More generally, we study the problem of finding the minimum number of links that a set of external influencers should form to people in the network, in order to activate the entire social network. This {\em Minimum Links} Problem has applications in viral marketing and the study of epidemics. Its solution can be…

FOS: Computer and information sciencesPhysics - Physics and SocietyGeneral Computer ScienceFOS: Physical sciencesPhysics and Society (physics.soc-ph)0102 computer and information sciences02 engineering and technology01 natural sciencesSocial networksGraphTheoretical Computer ScienceCombinatoricsComputer Science - Data Structures and AlgorithmsGreedy algorithmFOS: Mathematics0202 electrical engineering electronic engineering information engineeringMathematics - CombinatoricsData Structures and Algorithms (cs.DS)Greedy algorithmTime complexityNP-completeMathematicsSocial and Information Networks (cs.SI)Social networkDiscrete mathematicsBinary treeDegree (graph theory)Computer Science (all)Order (ring theory)Computer Science - Social and Information NetworksJoin (topology)Influence maximizationGreedy algorithms010201 computation theory & mathematicsGraphs; Greedy algorithms; Influence maximization; NP-complete; Social networksProduct (mathematics)020201 artificial intelligence & image processingCombinatorics (math.CO)Constant (mathematics)GraphsTheoretical Computer Science
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A permutation code preserving a double Eulerian bistatistic

2016

Visontai conjectured in 2013 that the joint distribution of ascent and distinct nonzero value numbers on the set of subexcedant sequences is the same as that of descent and inverse descent numbers on the set of permutations. This conjecture has been proved by Aas in 2014, and the generating function of the corresponding bistatistics is the double Eulerian polynomial. Among the techniques used by Aas are the M\"obius inversion formula and isomorphism of labeled rooted trees. In this paper we define a permutation code (that is, a bijection between permutations and subexcedant sequences) and show the more general result that two $5$-tuples of set-valued statistics on the set of permutations an…

FOS: Computer and information sciencesPolynomialDiscrete Mathematics (cs.DM)0102 computer and information sciences01 natural sciencesBijective proofCombinatoricsSet (abstract data type)symbols.namesakeEquidistributed sequence[MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO]FOS: MathematicsDiscrete Mathematics and CombinatoricsMathematics - Combinatorics0101 mathematicsComputingMilieux_MISCELLANEOUSMathematicsConjectureMathematics::CombinatoricsApplied Mathematics010102 general mathematicsGenerating functionEulerian path010201 computation theory & mathematicssymbolsBijectionCombinatorics (math.CO)Computer Science - Discrete Mathematics
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On prefix normal words and prefix normal forms

2016

A $1$-prefix normal word is a binary word with the property that no factor has more $1$s than the prefix of the same length; a $0$-prefix normal word is defined analogously. These words arise in the context of indexed binary jumbled pattern matching, where the aim is to decide whether a word has a factor with a given number of $1$s and $0$s (a given Parikh vector). Each binary word has an associated set of Parikh vectors of the factors of the word. Using prefix normal words, we provide a characterization of the equivalence class of binary words having the same set of Parikh vectors of their factors. We prove that the language of prefix normal words is not context-free and is strictly contai…

FOS: Computer and information sciencesPrefix codePrefix normal wordPre-necklaceDiscrete Mathematics (cs.DM)General Computer ScienceFormal Languages and Automata Theory (cs.FL)Binary numberComputer Science - Formal Languages and Automata TheoryContext (language use)Binary languageLyndon words0102 computer and information sciences02 engineering and technologyPrefix grammarprefix normal formsKraft's inequalityCharacterization (mathematics)Lyndon word01 natural sciencesPrefix normal formenumerationTheoretical Computer ScienceFOS: Mathematics0202 electrical engineering electronic engineering information engineeringMathematics - CombinatoricsMathematicsDiscrete mathematicsprefix normal words prefix normal forms binary languages binary jumbled pattern matching pre-necklaces Lyndon words enumerationbinary jumbled pattern matchingSettore INF/01 - InformaticaComputer Science (all)pre-necklacesComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)prefix normal wordsPrefix010201 computation theory & mathematics020201 artificial intelligence & image processingCombinatorics (math.CO)binary languagesComputer Science::Formal Languages and Automata TheoryWord (group theory)Computer Science - Discrete MathematicsTheoretical Computer Science
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Primitive sets of words

2020

Given a (finite or infinite) subset $X$ of the free monoid $A^*$ over a finite alphabet $A$, the rank of $X$ is the minimal cardinality of a set $F$ such that $X \subseteq F^*$. We say that a submonoid $M$ generated by $k$ elements of $A^*$ is {\em $k$-maximal} if there does not exist another submonoid generated by at most $k$ words containing $M$. We call a set $X \subseteq A^*$ {\em primitive} if it is the basis of a $|X|$-maximal submonoid. This definition encompasses the notion of primitive word -- in fact, $\{w\}$ is a primitive set if and only if $w$ is a primitive word. By definition, for any set $X$, there exists a primitive set $Y$ such that $X \subseteq Y^*$. We therefore call $Y$…

FOS: Computer and information sciencesPrimitive setDiscrete Mathematics (cs.DM)General Computer ScienceFormal Languages and Automata Theory (cs.FL)Pseudo-repetitionComputer Science - Formal Languages and Automata Theory0102 computer and information sciences02 engineering and technology01 natural sciencesTheoretical Computer ScienceCombinatoricsCardinalityFree monoidBi-rootFOS: Mathematics0202 electrical engineering electronic engineering information engineeringMathematics - CombinatoricsRank (graph theory)Primitive root modulo nMathematicsHidden repetitionSettore INF/01 - InformaticaIntersection (set theory)k-maximal monoidFunction (mathematics)Basis (universal algebra)010201 computation theory & mathematics020201 artificial intelligence & image processingCombinatorics (math.CO)Computer Science::Formal Languages and Automata TheoryWord (group theory)Computer Science - Discrete Mathematics
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Mahonian STAT on words

2016

In 2000, Babson and Steingrimsson introduced the notion of what is now known as a permutation vincular pattern, and based on it they re-defined known Mahonian statistics and introduced new ones, proving or conjecturing their Mahonity. These conjectures were proved by Foata and Zeilberger in 2001, and by Foata and Randrianarivony in 2006.In 2010, Burstein refined some of these results by giving a bijection between permutations with a fixed value for the major index and those with the same value for STAT , where STAT is one of the statistics defined and proved to be Mahonian in the 2000 Babson and Steingrimsson's paper. Several other statistics are preserved as well by Burstein's bijection.At…

FOS: Computer and information sciencesQA75[ INFO ] Computer Science [cs]Discrete Mathematics (cs.DM)Major index0102 computer and information sciencesMathematical Analysis01 natural sciencesWords and PermutationsCombinatorial problemsEquidistributionTheoretical Computer ScienceCombinatoricssymbols.namesakePermutationBijectionsFOS: MathematicsMathematics - CombinatoricsMathematical proofs[INFO]Computer Science [cs]0101 mathematicsStatisticMathematicsStatisticZ665Algebraic combinatoricsMathematics::CombinatoricsFormal power seriesPatternPermutationsEulerian path16. Peace & justiceComputer Science Applications010101 applied mathematics010201 computation theory & mathematicsCombinatoricsSignal ProcessingsymbolsBijectionCombinatorics (math.CO)Information SystemsComputer Science - Discrete Mathematics
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Quadratic speedup for finding marked vertices by quantum walks

2020

A quantum walk algorithm can detect the presence of a marked vertex on a graph quadratically faster than the corresponding random walk algorithm (Szegedy, FOCS 2004). However, quantum algorithms that actually find a marked element quadratically faster than a classical random walk were only known for the special case when the marked set consists of just a single vertex, or in the case of some specific graphs. We present a new quantum algorithm for finding a marked vertex in any graph, with any set of marked vertices, that is (up to a log factor) quadratically faster than the corresponding classical random walk.

FOS: Computer and information sciencesQuadratic growthQuantum PhysicsQuantum algorithmsSpeedupMarkov chainMarkov chainsProbability (math.PR)FOS: Physical sciencesRandom walkVertex (geometry)CombinatoricsQuadratic equationSearch by random walkQuantum searchComputer Science - Data Structures and AlgorithmsFOS: MathematicsData Structures and Algorithms (cs.DS)Quantum walkQuantum algorithmQuantum Physics (quant-ph)Mathematics - ProbabilityMathematicsQuantum walks
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