简介：Thispaperconsiderstheexistenceandasymptoticestimatesofglobalsolutionsandfinitetimeblowupoflocalsolutionofnon-Newtonfiltrationequationwithspecialmediumvoidofthefollowingform:{ut/|x|^2-△pu=u^q,(x,t)∈Ω×（0,T),u(x,t)=0,(x,t)∈ЭΩ×（0，T），u（x，0）=u0(x),u0(x)≥0,u0(x)全不等于0，where△pu=div(|△↓u|^p-2△↓u),ΩisasmoothboundeddomaininR^N(N≥3),0∈Ω,2

简介：在这篇论文，non-quasi-Newton“有用于非强迫的优化问题的不精确的线搜索的s家庭被学习。为non-quasi-Newton的一个新更改公式“sfamily被建议。如果，有任何一个Wolfe类型orArmijo类型线搜索的组成的算法全球性并且Q-superlinearly收敛，这被证明要最小化的功能hasLipschitz连续坡度。

简介：我们为最小化非强迫的光滑的凸的功能建议一个平行随机的牛顿方法(PSN)。我们在强烈凸的盒子中分析方法，并且给加速能在下面被期望的条件什么时候与它的连续对应物相比。我们显示出PSN怎么能一般来说被用于大二次的功能最小化，并且实验风险最小化问题。我们通过简单矩阵班的数字实验和模型表明方法的实际效率。

简介：ThispaperdiscussestheglobalexistenceandquenchingofthesolutiontotheNewtonfiltrationequationwiththenonlinearboundarycondition.Theauthorsalsodiscusstheprofileofthequenchingsolutioninthequenchingtimeandobtainthequenchingrateofthequenchingsolution.

简介：不精确的牛顿方法被把牛顿的方法与被用来不正确地解决牛顿方程的另一个反复的方法相结合构造。在这篇论文，我们为不精确的牛顿方法建立二条半本地人集中定理。当这二条定理被指定到牛顿的方法时，我们关于牛顿的方法获得一条不同Newton-Kantorovich定理。当为解决牛顿方程的反复的方法被指定是切开的方法时，我们为特殊不精确的牛顿方法关于重复步得到二估计。

简介：InthispaperwediscusstheconvergenceofamodifiedNewton’smethodpresentedbyA.Ostrowski[1]andJ.F.Traub[2],whichhasquadraticconvergenceorderbutreducesoneevaluationofthederivativeateverytwostepscomparedwithNewton’smethod.Aconvergencetheoremisestablishedbyusingaweakconditiona≤3-2(21/2)andasharperrorestimateisgivenabouttheiterativesequence.

简介：AconicNewtonmethodisattractivebecauseitconvergestoalocalminimizzerrapidlyfromanysufficientlygoodinitialguess.However,itmaybeexpensivetosolvetheconicNewtonequationateachiterate.InthispaperweconsideraninexactconicNewtonmethod,whichsolvesthecouicNewtonequationoldyapproximatelyandinsonmunspecifiedmanner.Furthermore,weshowthatsuchmethodislocallyconvergentandcharacterizestheorderofconvergenceintermsoftherateofconvergenceoftherelativeresiduals.

简介：伪--牛顿方程为解决非线性的方程或非强迫的优化问题的系统在quasi-Newtonmethods起了一个中央作用。相反，平底锅建议了一个新方程，并且当时，证明它具有第二份订单第一份订单传统，在某些近似意义。在这篇论文，我们做二个方程的归纳作为特殊情况包括他们。概括方程被分析，并且新更改从它被导出。象DFP一样新更改在一套标准测试问题的计算实验超过了traditionalDFP更改。

简介：Recentexperiencehasshownthatinterior-pointmethodsusingalogbarrierapproacharefarsuperiortoclassicalsimplexmethodsforcomputingsolutionstolargeparametricquantileregressionproblems.Inmanylargeempiricalapplications,thedesignmatrixhasaverysparsestructure.Atypicalexampleistheclassicalfixed-effectmodelforpaneldatawheretheparametricdimensionofthemodelcanbequitelarge,butthenumberofnon-zeroelementsisquitesmall.AdoptingrecentdevelopmentsinsparselinearalgebraweintroduceamodifiedversionoftheFrisch-NewtonalgorithmforquantileregressiondescribedinPortnoyandKoenker[28].Thenewalgorithmsubstantiallyreducesthestorage(memory)requirementsandincreasescomputationalspeed.Themodifiedalgorithmalsofacilitatesthedevelopmentofnonparametricquantileregressionmethods.Thepseudodesignmatricesemployedinnonparametricquantileregressionsmoothingareinherentlysparseinboththefidelityandroughnesspenaltycomponents.ExploitingthesparsestructureoftheseproblemsopensupawholerangeofnewpossibilitiesformultivariatesmoothingonlargedatasetsviaANOVA-typedecompositionandpartiallinearmodels.

简介：Thegeneralizedcomplementarityproblemincludesthewell-knownnonlinearcomplementarityproblemandlinearcomplementarityproblemasspecialcases.Inthispaper,basedonaclassofsmoothingfunctions,asmoothingNewton-typealgorithmisproposedforsolvingthegeneralizedcomplementarityproblem.Undersuitableassumptions,theproposedalgorithmiswell-definedandglobalconvergent.

简介：Analgorithmforsolvingaclassofsmoothconvexprogrammingisgiven.Usingsmoothexactmultiplierpenaltyfunction,asmoothconvexprogrammingisminimizedtoaminimizingstronglyconvexfunctiononthecompactsetwasreduced.ThenthestronglyconvexfunctionwithaNewtonmethodonthegivencompactsetwasminimized.

简介：从Newton运动学第二定律和Newton万有引力定律出发,导出Kepler行星绕日运动三定律.

简介：Inthispaper,aswitchingmethodforunconstrainedminimizationisproposed.ThemethodisbasedonthemodifiedBFGSmethodandthemodifiedSR1method.Theeigenvaluesandconditionnumbersofboththemodifiedupdatesareevaluatedandusedintheswitchingrule.WhentheconditionnumberofthemodifiedSR1updateissuperiortothemodifiedBFGSupdate,thestepintheproposedquasi-NewtonmethodisthemodifiedSR1step.OtherwisethestepisthemodifiedBFGSstep.Theefficiencyoftheproposedmethodistestedbynumericalexperimentsonsmall,mediumandlargescaleoptimization.Thenumericalresultsarereportedandanalyzedtoshowthesuperiorityoftheproposedmethod.

简介：WestudyhowtousetheSR1updatetorealizeminimizationmethodsforproblemswherethestorageiscritical.Wegiveanupdateformulawhichgeneratesmatricesusinginformationfromthelastmiterations.Thenumericaltestsshowthatthemethodisefficent.

简介：ThebasicprincipleofintervalarithmeticandthebasicalgorithmoftheintervalNewtonmethodsareintroduced.Theprototypealgorithmcannotfindanyzeroinanintervalthathaszerosometimes,thatis,itisinstable.Sotheprototyperelaxationprocedureisimprovedinthispaper.Additionally,animmediatetestoftheexistenceofasolutionfollowingbranch-and-boundisproposed,whichavoidsunwantedcomputationsinthoseintervalsthathavenosolution.ThenumericalresultsdemonstratthattheimprovedintervalNewtonmethodissuperiortoprototypealgorithmintermsofsolutionquality,stabilityandconvergentspeed.

简介：在这份报纸，我们考虑随机的线性补充问题(SLCP)的一个班与有限地许多元素。可行semismooth抑制了高斯牛顿算法因为SLCP被建议。建议算法的全球、局部地二次的集中在合适的条件下面被获得。一些数字结果在这份报纸被报导，它证实建议算法的好理论性质。

简介：Withtheemergenceoflocation-basedapplicationsinvariousfields,thehigheraccuracyofpositioningisdemanded.Byutilizingthetimedifferencesofarrival(TDOAs)andgainratiosofarrival(GROAs),anefficientalgorithmforestimatingthepositionisproposed,whichexploitstheBroyden-Fletcher-Goldfarb-Shanno(BFGS)quasi-Newtonmethodtosolvenonlinearequationsatthesourcelocationundertheadditivemeasurementerror.Althoughtheaccuracyoftwo-stepweighted-least-square(WLS)methodbasedonTDOAsandGROAsisveryhigh,thismethodhasahighcomputationalcomplexity.Whiletheproposedapproachcanachievethesameaccuracyandbiaswiththelowercomputationalcomplexitywhenthesignal-to-noiseratio(SNR)ishigh,especiallyitcanachievebetteraccuracyandsmallerbiasatalowerSNR.Theproposedalgorithmcanbeappliedtotheactualenvironmentduetoitsreal-timepropertyandgoodrobustperformance.Simulationresultsshowthatwithagoodinitialguesstobeginwith,theproposedestimatorconvergestothetruesolutionandachievestheCramer-Raolowerbound(CRLB)accuracyforbothnear-fieldandfar-fieldsources.

简介：WeprovideconvergenceresultsanderrorestimatesforNewton-likemethodsingeneralizedBanachspaces.TheideaofageneralizednormisusedwhichisdefinedtobeamapfromalinearspaceintoapartiallyorderedBanachspace.Convergenceresultsanderrorestimatesareimprovedcomparedwiththerealnormtheory.

简介：

简介：阐述Green公式、ostrogradsky-Gsuss公式stokes会式都是Newton-Leibniz公式在高维上的推广,进而推导出在高维上的Newton--leibniz公式．