简介:本文讨论了求解Sylvester方程AXB+CX=D的OROD迭代法(正交残量法和正交方向迭代法)的几个重要性质,证明了该算法产生的误差序列是单调递减的,同时给出了该算法的最小化性质的精确刻画,最后给出了一些数值例子.
简介:本文根据河北医科大学运用中药青风藤提取物青藤碱治疗患系膜增生性肾小球肾炎的SD大鼠的最新实验数据,采用多元统计分析的Fisher判别法.对该实验剥模过程、治疗效果进行判别分析,从统计意义上讲,该实验制模是成功的,青藤碱的治疗效果与常用药物雷公藤多苷一样比较显著.
简介:本文提出了求矩阵A的Jordan标准形的另一方法:利用rank(λ(E-A)^P的结果,得出了对应于特征(λi的Jordan块的阶数和个数,然后求出矩阵A的Jordan标准形.
简介:文[1]中提出了求解连续函数f(x)总体极小值的均值算法,并证明了算法的全局收敛性.若假设f(x)是定义在某可测集G上的可测函数,本文证明了均值算法产生的迭代序列全局收敛到f(x)的本质极小值,若进一步假设函数f(x)满足测度Lipschitz条件,还证明了求可测函数的均值算法是线性收敛的.
简介:通过构造拟上下解的单调迭代过程,在拟解对之间利用Sadvoskii不动点定理获得了Banach空间非线性三阶三点边值问题解的存在性.
简介:本文提出了求解非线性方程组的一种非精确Broyden方法.该方法是文献[8]中精确Broyden方法的推广.在适当的条件下,我们证明了非精确Broyden方法具有全局收敛性和超线性收敛性.数值实验表明,该方法效果较好.
简介:AinteriorpointscalingprojectedreducedHessianmethodwithcombinationofnonmonotonicbacktrackingtechniqueandtrustregionstrategyfornonlinearequalityconstrainedoptimizationwithnonegativeconstraintonvariablesisproposed.Inordertodealwithlargeproblems,apairoftrustregionsubproblemsinhorizontalandverticalsubspacesisusedtoreplacethegeneralfulltrustregionsubproblem.Thehorizontaltrustregionsubprobleminthealgorithmisonlyageneraltrustregionsubproblemwhiletheverticaltrustregionsubproblemisdefinedbyaparametersizeoftheverticaldirectionsubjectonlytoanellipsoidalconstraint.Bothtrustregionstrategyandlinesearchtechniqueateachiterationswitchtoobtainingabacktrackingstepgeneratedbythetwotrustregionsubproblems.Byadoptingthel1penaltyfunctionasthemeritfunction,theglobalconvergenceandfastlocalconvergencerateoftheproposedalgorithmareestablishedundersomereasonableconditions.AnonmonotoniccriterionandthesecondordercorrectionstepareusedtoovercomeMaratoseffectandspeeduptheconvergenceprogressinsomeill-conditionedcases.
简介:Thispaperdiscussestheintervalestimationsmethodfortheparametersandotherreliabilitycharactersofathree-poxameterWeibulldistribution.Accordingtothefiducialdistrlbutiontheoryoftheparameter,theauthorpresentstheconfidenceintervalsoftheporameters,thereliabilityandthereliablelife.Anexamplemadsimulationresultsaregiven.Itisshownthatthemethodpresentedinthispaperispracticableandworthnoticing.