搜索结果: 1-15 共查到“知识库 实变函数论”相关记录168条 . 查询时间(2.187 秒)
Berge极大值逆定理与Nash平衡定理
Berge极大值逆定理 Nash平衡定理 拟变分不等式 Von Neumann引理 Gale-Nikaido-Debreu引理的推广定理 伪连续
2019/4/17
本文运用Berge极大值逆定理和Nash平衡定理,通过构造适当的支付函数,直接推导出了拟变分不等式、广义变分不等式、Von Neumann引理,以及Gale-Nikaido-Debreu引理的推广定理.同时也提供了一个将上半连续凸紧值的集值映射问题转化为一个二元函数来处理的方法.这些结果和证明方法都是新的.
随机SIR流行病模型解的渐近性态
It公式 Lyapunov函数 随机干扰 SIR模型 渐近行为
2018/10/8
研究了一类随机SIR流行病模型.构建合适的Lyapunov函数,利用It公式,得出了该模型正解的全局存在唯一性;在该结论的基础上,讨论了随机模型的无病平衡点的渐近行为.在一些条件下,得出随机模型解的上确极限的最大值.
Constrained ordination analysis with flexible response functions
Canonical correspondence analysis Density estimation
2015/8/20
Canonical correspondence analysis (CCA) is perhaps the most popular multivariate technique used by environmental ecologists
for constrained ordination; it is an approximation to the maximum likelihoo...
Key Homomorphic PRFs and Their Applications
Pseudorandom functions Key homomorphism Non-uniform learning with errors
2015/8/5
A pseudorandom function F : K X ! Y is said to be key homomorphic if given F(k1; x)
and F(k2; x) there is an ecient algorithm to compute F(k1 k2; x), where denotes a group
operation on k1 and ...
在合理利用已有测试数据形成优势初始种群的前提下采用遗传算法自动生成回归测试数据是软件测试研究的一个热点.本文通过在已有测试数据的基础上依据MC/DC准则演进增补部分用例提升MC/DC覆盖率.首先,通过记录每个已有测试数据覆盖的条件组合确定要增补用例的目标条件组合,其次,根据适应度函数从已有测试数据中筛选出部分数据作为初始种群,再次,根据已筛选的部分初始种群所覆盖的条件组合与目标条件组合确定遗传操作...
用于高动态范围图像生成的CCD辐照度标定
高动态范围图像 CCD 辐照度标定 能量函数
2014/3/6
为了使低动态范围(LDR)图像采集设备能够生成高动态范围(HDR)图像,研究了对同一场景进行多次曝光生成HDR图像的技术,提出了不苛求输入图像为低噪声的CCD辐照度标定方法。为避免参数个数过多导致参数求解偏离全局最优值,构建了大幅削减参数个数的能量函数,该能量函数由CCD辐照度响应曲线参数模型、残差惩罚函数、权重函数3部分组成;分别使用低拟合误差的EMoR参数模型、抑制图像高斯噪声的平方和残差惩罚...
平面上凸曲线组合流
曲率流C&infin 范数凸曲线 撑函数
2013/12/4
主要研究了两种新的平面凸曲率流: 一种是由保面积流和保长度流组合而成, 这种曲率流在演化过程中缩短了曲线的周长, 增大了曲线所围成的面积; 另一种是两种保长度流的“凸组合”, 这种曲率流的周长是常数, 而面积不断增大. 两种曲率流都具有全局存在性, 并且当时间趋于无穷大时, 曲线在C∞范数下收敛到有限圆.
On removability properties of $ψ$-uniform domains in Banach spaces
Uniform domain uniform domain removability property quasihyperbolic metric
2012/6/9
Suppose that $E$ and $E'$ denote real Banach spaces with the same dimension at least 2. The main aim of this paper is to show that a domain $D$ in $E$ is a $\psi$-uniform domain if and only if $D\back...
崔贵珍在有理函数动力系统取得重要进展
崔贵珍 有理函数动力系统 重要进展
2011/10/9
对有理函数动力系统研究有十年之久的国家数学与交叉科学中心研究员崔贵珍近日在有理函数动力系统取得重要进展。他给出了几何有限有理函数的拓扑特征,并进一步研究了几何有限的有理函数的形变理论,利用这些理论并结合他们新发展的一个偏差定理, 进一步研究了有理函数的形变与分歧,以及双曲分支的结构,刻画了双曲分支边界的性质。
Anomalous scaling and generic structure function in turbulence
generic structure function Anomalous scaling exponential self-similar
2011/7/7
We discuss on an example a general mechanism of apparition of anomalous scaling in scale invariant systems via zero modes of a scale invariant operator. We discuss the relevance of such mechanism in t...
Perfect nonlinear functions from a finite group G to another one H are those functions f : G → H such that for all nonzero ∈ G, the derivative df : x 7→f(x)f(x)−1 is balanced.
Equivalence of concentration inequalities for linear and non-linear functions
concentration of measure large deviations quasiconvexity
2010/12/13
We consider a random variable X that takes values in a (possibly infinite-dimensional) topological vector space X. We show that, with respect to an appropriate “normal distance” on X.
On ASEP with Periodic Step Bernoulli Initial Condition
ASEP Periodic Step Bernoulli Initial Condition
2010/12/3
In the asymmetric simple exclusion process (ASEP) on the integers Z a particle waits exponential time, then moves to the right with probability p if that site is unoccupied (or else stays put) or to t...
To any walk in a quiver, we associate a Laurent polynomial. When the walk is the string of a string module over a 2-Calabi-Yau tilted algebra, we prove that this Laurent polynomial coincides with the ...
Derivative Formula and Applications for Hyperdissipative Stochastic Navier-Stokes/Burgers Equations
Bismut formula coupling strong Feller stochastic Navier-Stokes equation
2010/12/1
By using coupling method, a Bismut type derivative formula is established for the Markov semigroup associated to a class of hyperdissipative stochastic Navier-Stokes/Burgers equations. As applications...