Search results for "binary [neutron star]"

showing 10 items of 544 documents

A Loopless Generation of Bitstrings without p Consecutive Ones

2001

Let F n (p) be the set of all n-length bitstrings such that there are no p consecutive ls. F n (p) is counted with the pth order Fibonacci numbers and it may be regarded as the subsets of {1, 2,…, n} without p consecutive elements and bitstrings in F n (p) code a particular class of trees or compositions of an integer. In this paper we give a Gray code for F n (p) which can be implemented in a recursive generating algorithm, and finally in a loopless generating algorithm.

CombinatoricsGray codeSet (abstract data type)Discrete mathematicssymbols.namesakeCode (set theory)Fibonacci numberBinary treeIntegersymbolsOrder (group theory)Hamiltonian pathMathematics
researchProduct

An algorithm for the solution of tree equations

1997

We consider the problem of solving equations over k-ary trees. Here an equation is a pair of labeled α-ary trees, where α is a function associating an arity to each label. A solution to an equation is a morphism from α-ary trees to k-ary trees that maps the left and right hand side of the equation to the same k-ary tree.

CombinatoricsMorphismBinary treeBranch and boundSearch algorithmTree (set theory)Function (mathematics)ArityComputer Science::Information TheoryMathematicsEquation solving
researchProduct

Hyperidentities of some generalizations of lattices

1998

In the paper we present bases and hyperbases of hyperidentities of some generalizations of the variety L of all lattices and the variety D of distributive lattices. We describe the form of hyperidentities of some varieties with two binary operations.

CombinatoricsPure mathematicsAlgebra and Number TheoryDistributive propertyBinary operationHigh Energy Physics::LatticeLattice (order)Distributive latticeMathematicsAlgebra Universalis
researchProduct

Basic Definitions and Facts

2001

Symbol is treated here as a primitive entity as point or line in geometry. Let Con = {f α : α < β} be a well-ordered set of symbols called a language type. β is an ordinal number. The elements of the above set are called connectives. To each connective f α a natural number α(α) ∈ w called the rank of f α or the arity of f α is assigned. The arity α(α) defines the number of arguments of f α . Thus we speak of nullary, unary, or binary connectives, etc. In the sequel Con is assumed to be fixed but arbitrary.

CombinatoricsSet (abstract data type)Unary operationSymbol (programming)Binary numberOrdinal numberNatural numberRank (differential topology)ArityMathematics
researchProduct

Lesion of areas 17/18/19: effects on the cat's performance in a binary detection task

1988

The ability of two cats to discriminate between two geometrical outline patterns in the presence of superimposed Gaussian visual noise — i.e. in a binary detection task — was tested before and after bilateral removal of cortical areas 17, 18 and 19. The detection probability PD was measured as a function of the signal-to-noise ratio. After a lesion of areas 17, 18 and 19 both cats were unable to carry out the discrimination tasks. Their detection performance dropped to chance level, but after an extensive phase of retraining (3 months) they regained the ability to discriminate visual patterns. It was thus possible to obtain detection curves and to determine a measure of a performance which …

CommunicationCATSbusiness.industryGeneral NeuroscienceBrainBinary numberPattern recognitionForm PerceptionLesionTask (computing)Discrimination PsychologicalPattern Recognition VisualVisual patternsCatsImage noisemedicineAnimalsLearningDetection performanceFemaleArtificial intelligencemedicine.symptombusinessVisual CortexMathematicsExperimental Brain Research
researchProduct

On the Computational Complexity of Binary and Analog Symmetric Hopfield Nets

2000

We investigate the computational properties of finite binary- and analog-state discrete-time symmetric Hopfield nets. For binary networks, we obtain a simulation of convergent asymmetric networks by symmetric networks with only a linear increase in network size and computation time. Then we analyze the convergence time of Hopfield nets in terms of the length of their bit representations. Here we construct an analog symmetric network whose convergence time exceeds the convergence time of any binary Hopfield net with the same representation length. Further, we prove that the MIN ENERGY problem for analog Hopfield nets is NP-hard and provide a polynomial time approximation algorithm for this p…

Computational complexity theoryCognitive NeuroscienceComputationBinary numberHopfield networkTuring machinesymbols.namesakeRecurrent neural networkArts and Humanities (miscellaneous)Convergence (routing)symbolsTime complexityAlgorithmMathematicsNeural Computation
researchProduct

Equivalence closure in the two-variable guarded fragment

2015

We consider the satisfiability and finite satisfiability problems for the extension of the two-variable guarded fragment in which an equivalence closure operator can be applied to two distinguished binary predicates. We show that the satisfiability and finite satisfiability problems for this logic are 2-ExpTime-complete. This contrasts with an earlier result that the corresponding problems for the full two-variable logic with equivalence closures of two binary predicates are 2-NExpTime-complete.

Computational complexity theoryLogiccomputational complexityguarded fragmentsatisfiability problemBinary numberTheoretical Computer ScienceCombinatoricsArts and Humanities (miscellaneous)Computer Science::Logic in Computer ScienceClosure operatorEquivalence (formal languages)MathematicsDiscrete mathematicssatisfiability problemcomputational complexitydecidabilityequivalence closureSatisfiabilityDecidabilityTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESClosure (computer programming)Hardware and ArchitectureTheoryofComputation_LOGICSANDMEANINGSOFPROGRAMSBoolean satisfiability problemSoftwareJournal of Logic and Computation
researchProduct

Support Vector Machine and Kernel Classification Algorithms

2018

This chapter introduces the basics of support vector machine (SVM) and other kernel classifiers for pattern recognition and detection. It also introduces the main elements and concept underlying the successful binary SVM. The chapter starts by introducing the main elements and concept underlying the successful binary SVM. Next, it introduces more advanced topics in SVM for classification, including large margin filtering (LMF), SSL, active learning, and large‐scale classification using SVMs. The LMF method performs both signal filtering and classification simultaneously by learning the most appropriate filters. SSL with SVMs exploits the information contained in both labeled and unlabeled e…

Computer Science::Machine LearningOptimization problemActive learning (machine learning)business.industryComputer scienceBinary numberPattern recognitionSupport vector machineStatistical classificationComputingMethodologies_PATTERNRECOGNITIONMargin (machine learning)Kernel (statistics)Pattern recognition (psychology)Artificial intelligencebusiness
researchProduct

A GPU-Based DVC to H.264/AVC Transcoder

2010

Mobile to mobile video conferencing is one of the services that the newest mobile network operators can offer to users With the apparition of the distributed video coding paradigm which moves the majority of complexity from the encoder to the decoder, this offering can be achieved by introducing a transcoder This device has to convert from the distributed video coding paradigm to traditional video coding such as H.264/AVC which is formed by simpler decoders and more complex encoders, and allows to the users to execute only the low complex algorithms In order to deal with this high complex video transcoder, this paper introduces a graphics processing unit based transcoder as base station The…

Computer architectureComputer scienceVideo trackingReal-time computingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONData_CODINGANDINFORMATIONTHEORYVideo processingMultiview Video CodingCoding tree unitEncoderContext-adaptive binary arithmetic codingScalable Video CodingVideo compression picture types
researchProduct

Influence Diagnostics for Meta-Analysis of Individual Patient Data Using Generalized Linear Mixed Models

2014

In meta-analysis, generalized linear mixed models (GLMMs) are usually used when heterogeneity is present and individual patient data (IPD) are available, while accepting binary, discrete as well as continuous response variables. In the present paper some measures of influence diagnostics based on log-likelihood are suggested and discussed. A known measure is approximated to get a simpler form, for which the information matrix is no more necessary. The performance of the proposed measure is assessed through a diagnostic analysis on simulated data reproducing a possible meta-analytical context of IPD with influential outliers. The proposed measure is showed to work well and to have a form sim…

Computer scienceBinary numberContext (language use)Diagnostics Individual Patient Data Meta-Analysis OutliersMeasure (mathematics)Generalized linear mixed modelsymbols.namesakeMeta-analysisOutlierStatisticssymbolsSettore SECS-S/01 - StatisticaFisher informationAlgorithmStatistic
researchProduct