Search results for "Analysis of algorithm"

showing 10 items of 29 documents

A comprehensive probabilistic analysis of approximate SIR‐type epidemiological models via full randomized discrete‐time Markov chain formulation with…

2020

Spanish Ministerio de Economia y Competitividad, Grant/Award Number: MTM2017-89664-P; Generalitat Valenciana, Grant/Award Number: APOSTD/2019/128; Ministerio de Economia y Competitividad, Grant/Award Number: MTM2017-89664-P

010101 applied mathematicsDiscrete mathematicsMarkov chainDiscrete time and continuous timeGeneral Mathematics010102 general mathematicsGeneral EngineeringProbabilistic analysis of algorithms0101 mathematicsType (model theory)01 natural sciencesMathematicsMathematical Methods in the Applied Sciences
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A Probabilistic Analysis to Quantify the Effect of March 11, 2004, Attacks in Madrid on the March 14 Elections in Spain: A Dynamic Modelling Approach

2015

[EN] The bomb attacks in Madrid three days before the general elections of March 14, 2004, and their possible influence on the victory of PSOE (Spanish Workers Socialist Party), defeating PP (Popular Party), have been a matter of study from several points of view (i.e., sociological, political, or statistical). In this paper, we present a dynamic model based on a system of differential equations such that it, using data from Spanish CIS (National Center of Sociological Research), describes the evolution of voting intention of the Spanish people over time. Using this model, we conclude that the probability is very low that the PSOE would have won had the attack not happened.Moreover, after t…

Article SubjectOperations researchlcsh:MathematicsApplied Mathematicsmedia_common.quotation_subjectSociological researchVictoryDynamic modellinglcsh:QA1-939PoliticsEconomyVotingGeneral electionProbabilistic analysis of algorithmsCenter (algebra and category theory)MATEMATICA APLICADAAnalysisMathematicsmedia_commonAbstract and Applied Analysis
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Estimation of Granger causality through Artificial Neural Networks: applications to physiological systems and chaotic electronic oscillators

2021

One of the most challenging problems in the study of complex dynamical systems is to find the statistical interdependencies among the system components. Granger causality (GC) represents one of the most employed approaches, based on modeling the system dynamics with a linear vector autoregressive (VAR) model and on evaluating the information flow between two processes in terms of prediction error variances. In its most advanced setting, GC analysis is performed through a state-space (SS) representation of the VAR model that allows to compute both conditional and unconditional forms of GC by solving only one regression problem. While this problem is typically solved through Ordinary Least Sq…

Artificial neural networks; Chaotic oscillators; Granger causality; Multivariate time series analysis; Network physiology; Penalized regression techniques; Remote synchronization; State-space models; Stochastic gradient descent L1; Vector autoregressive modelGeneral Computer ScienceDynamical systems theoryComputer science02 engineering and technologyChaotic oscillatorsPenalized regression techniquesNetwork topologySettore ING-INF/01 - ElettronicaMultivariate time series analysisVector autoregression03 medical and health sciences0302 clinical medicineScientific Computing and Simulation0202 electrical engineering electronic engineering information engineeringRepresentation (mathematics)Optimization Theory and ComputationNetwork physiologyState-space modelsArtificial neural networkArtificial neural networksData ScienceTheory and Formal MethodsQA75.5-76.95Stochastic gradient descent L1Granger causality State-space models Vector autoregressive model Artificial neural networks Stochastic gradient descent L1 Multivariate time series analysis Network physiology Remote synchronization Chaotic oscillators Penalized regression techniquesRemote synchronizationStochastic gradient descentAutoregressive modelAlgorithms and Analysis of AlgorithmsVector autoregressive modelElectronic computers. Computer scienceSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaGranger causality020201 artificial intelligence & image processingGradient descentAlgorithm030217 neurology & neurosurgeryPeerJ Computer Science
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A method for the probabilistic analysis of nonlinear systems

1995

Abstract The probabilistic description of the response of a nonlinear system driven by stochastic processes is usually treated by means of evaluation of statistical moments and cumulants of the response. A different kind of approach, by means of new quantities here called Taylor moments, is proposed. The latter are the coefficients of the Taylor expansion of the probability density function and the moments of the characteristic function too. Dual quantities with respect to the statistical cumulants, here called Taylor cumulants, are also introduced. Along with the basic scheme of the method some illustrative examples are analysed in detail. The examples show that the proposed method is an a…

Characteristic function (probability theory)Stochastic processMechanical EngineeringAerospace EngineeringOcean EngineeringStatistical and Nonlinear PhysicsProbability density functionCondensed Matter Physicssymbols.namesakeNonlinear systemNuclear Energy and EngineeringTaylor seriessymbolsCalculusApplied mathematicsProbabilistic analysis of algorithmsCumulantCivil and Structural EngineeringMathematicsTaylor expansions for the moments of functions of random variables
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Fast and Simple Approximation of the Diameter and Radius of a Graph

2006

The increasing amount of data to be processed by computers has led to the need for highly efficient algorithms for various computational problems. Moreover, the algorithms should be as simple as possible to be practically applicable. In this paper we propose a very simple approximation algorithm for finding the diameter and the radius of an undirected graph. The algorithm runs in $O(m\sqrt{n})$ time and gives an additive error of $O(\sqrt{n})$ for a graph with n vertices and m edges. Practical experiments show that the results of our algorithm are close to the optimum and compare favorably to the 2/3-approximation algorithm for the diameter problem by Aingworth et al [1].

CombinatoricsTheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITYGraph (abstract data type)Approximation algorithmAlgorithm engineeringRadiusComputational problemStrength of a graphDistanceMathematicsofComputing_DISCRETEMATHEMATICSAnalysis of algorithmsMathematics
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Centering and Compound Conditionals under Coherence

2016

There is wide support in logic , philosophy , and psychology for the hypothesis that the probability of the indicative conditional of natural language, \(P(\textit{if } A \textit{ then } B)\), is the conditional probability of B given A, P(B|A). We identify a conditional which is such that \(P(\textit{if } A \textit{ then } B)= P(B|A)\) with de Finetti’s conditional event, B|A. An objection to making this identification in the past was that it appeared unclear how to form compounds and iterations of conditional events. In this paper, we illustrate how to overcome this objection with a probabilistic analysis, based on coherence, of these compounds and iterations. We interpret the compounds a…

Discrete mathematicsIndicative conditionalcenteringSettore MAT/06 - Probabilita' E Statistica Matematica05 social sciencesClassical logicConditional probabilityInference02 engineering and technologyCoherence (philosophical gambling strategy)p-entailmentn-conditional event050105 experimental psychologycoherenceLogical biconditionalp-validity0202 electrical engineering electronic engineering information engineeringbiconditional event020201 artificial intelligence & image processing0501 psychology and cognitive sciencesProbabilistic analysis of algorithmsArithmeticMathematicsEvent (probability theory)Conditional
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A Probabilistic Approach to the Count-To-Infinity Problem in Distance-Vector Routing Algorithms

2013

Count-to-infinity problem is characteristic for routing algorithms based on the distributed implementation of the classical Bellman-Ford algorithm. In this paper a probabilistic solution to this problem is proposed. It is argued that by the use of a Bloom Filter added to the routing message the routing loops will with high probability not form. An experimental analysis of this solution for use in Wireless Sensor Networks in practice is also included.

Distance-vector routing protocolLink-state routing protocolComputer scienceAnt colony optimization algorithmsComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKSMultipath routingComputer Science::Networking and Internet ArchitectureProbabilistic logicPath vector protocolProbabilistic analysis of algorithmsRouting (electronic design automation)Algorithm
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On the Greedy Algorithm for the Shortest Common Superstring Problem with Reversals

2015

We study a variation of the classical Shortest Common Superstring (SCS) problem in which a shortest superstring of a finite set of strings $S$ is sought containing as a factor every string of $S$ or its reversal. We call this problem Shortest Common Superstring with Reversals (SCS-R). This problem has been introduced by Jiang et al., who designed a greedy-like algorithm with length approximation ratio $4$. In this paper, we show that a natural adaptation of the classical greedy algorithm for SCS has (optimal) compression ratio $\frac12$, i.e., the sum of the overlaps in the output string is at least half the sum of the overlaps in an optimal solution. We also provide a linear-time implement…

FOS: Computer and information sciences0102 computer and information sciences02 engineering and technologyInformation System01 natural sciencesString (physics)Theoretical Computer ScienceCombinatoricsHigh Energy Physics::TheoryAnalysis of algorithmGreedy algorithmComputer Science - Data Structures and Algorithms0202 electrical engineering electronic engineering information engineeringData Structures and Algorithms (cs.DS)Greedy algorithmFinite setAnalysis of algorithmsMathematicsSuperstring theoryShortest Common SuperstringComputer Science Applications1707 Computer Vision and Pattern RecognitionComputer Science ApplicationsReversalShortest Path Faster Algorithm010201 computation theory & mathematicsCompression ratioSignal Processing020201 artificial intelligence & image processingK shortest path routingInformation Systems
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Quasi conjunction, quasi disjunction, t-norms and t-conorms: Probabilistic aspects

2013

We make a probabilistic analysis related to some inference rules which play an important role in nonmonotonic reasoning. In a coherence-based setting, we study the extensions of a probability assessment defined on $n$ conditional events to their quasi conjunction, and by exploiting duality, to their quasi disjunction. The lower and upper bounds coincide with some well known t-norms and t-conorms: minimum, product, Lukasiewicz, and Hamacher t-norms and their dual t-conorms. On this basis we obtain Quasi And and Quasi Or rules. These are rules for which any finite family of conditional events p-entails the associated quasi conjunction and quasi disjunction. We examine some cases of logical de…

FOS: Computer and information sciencesSettore MAT/06 - Probabilita' E Statistica MatematicaInformation Systems and ManagementComputer Science - Artificial Intelligencet-Norms/conormDuality (mathematics)goodman-nguyen inclusion relation; lower/upper probability bounds; t-norms/conorms; generalized loop rule; coherence; quasi conjunction/disjunctionComputer Science::Artificial IntelligenceTheoretical Computer ScienceArtificial IntelligenceFOS: MathematicsProbabilistic analysis of algorithmsNon-monotonic logicRule of inferenceLower/upper probability boundGoodman–Nguyen inclusion relationMathematicsEvent (probability theory)Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniDiscrete mathematicsInterpretation (logic)Probability (math.PR)Probabilistic logicCoherence (philosophical gambling strategy)Generalized Loop ruleComputer Science ApplicationsAlgebraArtificial Intelligence (cs.AI)Control and Systems EngineeringQuasi conjunction/disjunctionCoherenceMathematics - ProbabilitySoftwareInformation Sciences
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Complexity of probabilistic versus deterministic automata

2005

Finite-state machineNested wordTheoretical computer scienceDFA minimizationDeterministic automatonComputer scienceDeterministic context-free grammarAutomata theoryQuantum finite automataProbabilistic analysis of algorithms
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