学科分类
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38 个结果
  • 简介:Themaximummatchinggraphofagraphhasavertexforeachmaximummatchingandanedgeforeachpairofmaximummatchingswhichdifferbyexactlyoneedge.Inthispaper,weobtainalowerboundofdistancebetweentwoverticesofmaximummatchinggraph,andgiveanecessaryandsufficientconditionthattheboundcanbereached.

  • 标签: 最大匹配图 距离 正盈余 组合优化
  • 简介:精力最小化广泛地被使用了在象电脑辅助的几何设计那样的地里构造曲线和表面,计算机图形。然而,我们的严峻的例子证明精力最小化不有时优化曲线的形状。这份报纸学习在最小化紧张精力和曲线形状之间的关系,学习被与令人满意的形状构造一条立方的Hermite曲线执行。立方的Hermite曲线插入内推二个给定的端点的位置和正切向量。计算机模拟技术成为了科学发现的方法之一,学习进程被数字计算和计算机模拟技术执行。我们的结果显示出那:(1)立方的Hermite曲线不能被完全最小化紧张精力构造;(2)紧张精力由本地最小的采纳珍视,立方的Hermite曲线的形状能为大约60%所有情况被决定,其中一些然而有不能令人满意的形状。基于种类精力模型和分析,一个新模型为与令人满意的形状构造立方的Hermite曲线被介绍,它是种类精力的修正模型。新模型使用一个明确的公式计算二正切向量的大小,并且有性质:(1)计算是容易的;(2)它让立方的Hermite曲线当保持在曲线建设为一些盒子最小化种类精力的好性质时,有令人满意的形状。与最小的种类精力模型一起的新模型的比较被包括。

  • 标签: 曲线形状 HERMITE曲线 计算机辅助几何设计 计算机模拟技术 计算机仿真技术 能量模型
  • 简介:ThelargescalelinearsystemswithM-matricesoftenappearinawidevarietyofareasofphysical,fluiddynamicsandeconomicsciences.Itisreportedin[1]thattheconvergencerateoftheIMGSmethod,withthepreconditionerI+S_α,issuperiortothatofthebasicSORiterativemethodfortheM-matrix.ThispaperconsidersthepreconditionedJacobi(PJ)methodwiththepreconditionerP=I+S_α+S_β,andprovestheoreticallythattheconvergencerateofthePJmethodisbetterthanthatofthebasicAORmethod.Numericalexamplesareprovidedtoillustratethemainresultsobtained.

  • 标签: 雅可比行列式 迭代法 前提条件 最大矩阵
  • 简介:纸基于准确公平可靠,相对错误函数作为损失功能在被拿开发最佳的Bonus-Malus系统(BMS)的一个图案。在BMS,频率和严厉部件被考虑。这个图案与从古典方形错误的损失功能导出的传统的BMS相比。

  • 标签: Bonus-Malus系统 BMS 差积可靠性 公平可靠性 误差函数
  • 简介:Ithasbeenevidentthatthetheoryandmethodsofdynamicderivativesareplayinganincreasinglyimportantrleinhybridmodelingandcomputations.Beingconstructedonvariouskindsofhybridgrids,thatis,timescales,dynamicderivativesoffersuperioraccuracyandflexibilityinapproximatingmathematicallyimportantnat-uralprocesseswithhard-to-predictsingularities,suchastheepidemicgrowthwithun-predictablejumpsizesandoptionmarketchangeswithhighuncertainties,ascom-paredwithconventionalderivatives.Inthisarticle,weshallreviewthenovelnewconcepts,exploredelicaterelationsbetweenthemostfrequentlyusedsecond-orderdy-namicderivativesandconventionalderivatives.Weshallinvestigatenecessarycondi-tionsforguaranteeingtheconsistencybetweenthetwoderivatives.Wewillshowthatsuchaconsistencymayneverexistingeneral.Thisimpliesthatthedynamicderivativesprovideentirelydifferentnewtoolsforsensitivemodelingandapproximationsonhy-bridgrids.Rigorouserroranalysiswillbegivenviaasymptoticexpansionsforfurthermodelingandcomputationalapplications.Numericalexperimentswillalsobegiven.

  • 标签: 误差估计 逼近 混合网格 一致性
  • 简介:Forapolynomialp(z)ofdegreenwhichhasnozerosin|z|<1,Dewanetal.,(K.K.DewanandSunilHans,Generalizationofcertainwellknownpolynomialinequalities,J.Math.Anal.Appl.,363(2010),38–41)establishedzp′(z)+nβ2p(z)≤n2{(β2+1+β2)max|z|=1|p(z)|-(1+β2-β2)min|z|=1|p(z)|},foranycomplexnumberβwith|β|≤1and|z|=1.InthispaperweconsidertheoperatorB,whichcarriesapolynomialp(z)intoB[p(z)]:=λ0p(z)+λ1(nz2)p′(z)1!+λ2(nz2)2p′′(z)2!,whereλ0,λ1,andλ2aresuchthatallthezerosofu(z)=λ0+c(n,1)λ1z+c(n,2)λ2z2lieinthehalfplane|z|≤|z-n/2|.ByusingtheoperatorB,wepresentageneralizationofresultofDewan.Ourresultgeneralizescertainwell-knownpolynomialinequalities.

  • 标签: 多项式 不等式 操作 运营商 零点 数学
  • 简介:MultidimensionalTimeModelforProbabilityCumulativeFunctioncanbereducedtofinite-dimensionaltimemodel,whichcanbecharacterizedbyBooleanalgebraforoperationsovereventsandtheirprobabilitiesandindexsetforreductionofinfinitedimensionaltimemodeltofinitenumberofdimensionsoftimemodelconsideringalsothefractal-dimensionaltimearisingfromalikesupersymmetricalpropertiesofprobability.Thiscanleadtovariousapplicationsforparameterevaluationandriskreductioninsuchbigcomplexdatastructuresascomplexdependencestructures,images,networks,andgraphs,missingandsparsedata,suchastocomputervision,biology,medicine,andvariousDNAanalyses.

  • 标签: finite-dimensional time model normally distributed COMPLETE
  • 简介:AbstracthomornorphismsbetweensubgroupsofalgebraicgroupswerestudiedindetailbyA.Borel,J.Tits^(1)andB.Weisfeiler^(2)providedthattheimagesofthehomomorphismsareZariskidensesubsetsandthatthefieldsoverwhichalgebraiegroupsaredefinedareinfinite,ThepurposeofthispaperistodetermineallembeddinghomomorphismsofSLn(κ)intoSLn(K)whenκandKareanyfieldsofthesamecharacteristic,withoutassumptionofZariskidensityandinfinitudeoffields.TheresultinthispapergeneralizesaresultofChenYuonhomomorphismsoftwodimensionallineargroups^(3).

  • 标签: 经典群论 同态 域论 特殊线性群 可除环
  • 简介:TwoclassesofMallowsGM-estimatorswithinvarianceareconsideredinthestochasticlinearregressionmodel.Someoftheirasymptoticpropertiesaredescribed,andthefittedvalueinfluenceandvariancecomponentsarecomparedbymeansofrobustcovariances,

  • 标签: GM-估计 统计线性回归模型 渐进性质 强协方差
  • 简介:LetEandFbeBanachspacesandfnon-linearC^1mapfromEintoF.ThemainresultisTheorem2.2,inwhichaconnectionbetweenlocalconjugacyproblemoffatx0∈Eandalocalfinepropertyoff'(x)atx0(seetheDefinition1.1inthispaper)areobtained.Thistheoremincludesasspecialcasesthetwoknowntheorems:thefiniteranktheoremandBerger'sTheoremfornon-linearFredholmoperators.Moreover:thetheoremgivesrisethefurtherresultsforsomenon-linearsemi-Fredholmmapsandforallnon-linearsemi-FredholmmapswhenEandFareHilbertspaces.ThusTheorem2.2notonlyjustunifiestheaboveknowntheoremsbutalsoreallygeneralizesthem.

  • 标签: 非线性半弗雷德霍姆映射 反转算子 巴拿赫空间 局部共轭性
  • 简介:Inthispaper,theconceptoftheinfinitesimalrealizationfactorisextendedtotheparameter-dependentperformancefunctionsinclosedqueueingnetworks.Thentheconceptsofrealizationmatrix(itselementsarecalledrealizationfactors)andperformancepotentialareintroduced,andtherelationsbetweeninfinitesimalrealizationfactorsandthesetwoquantitiesarediscussed.ThisprovidesaunitedframeworkforbothIPAandnonIPAapproaches.Finally,anotherphysicalmeaningoftheservicerateisgiven.

  • 标签: 闭排队网络 性能势 功能函数 无穷小实现因子
  • 简介:ForananalyticfunctionfonthehyperbolicdomainΩinC,thefollowingconclusionsareobtained:(i)f∈B(Ω)=BMOA(Ω,m)ifandonlyifRef∈B(?)(Ω)=BMOH(Ω,m).(ii)QB_h(Ω)=B_h(Ω)(BMOH,(Ω,m)=BMOH(Ω,m)ifandonlyifC(Ω)=inf{Z_o(z)·δ_o(z)·z≡Ω}>0,Alsosomeapplica-lionstoautomorphicfunctionareconsidered.

  • 标签: HYPERBOLIC analytic Riemann BLOCH conclusions proof