Translation surfaces in the 3-dimensional space satisfying Δ III r i = μ i r i

In this paper we study the translation surfaces in the 3-dimensional Euclidean and Lorentz-Minkowski space under the condition ${\Delta ^{III}r_{i} = \mu _{i}r_{i},\mu _{i} \in \mathbb{R}}$ , where Δ ^III denotes the Laplacian of the surface with respect to the third fundamental form III. We show that in both spaces a translation surface satisfying the preceding relation is a surface of Scherk.     

A Note on the Difference Equation x n +1 = ∑ i =0 k α i x n − i p i

In this note we improve Theorem 2 in Ref. [3] , about the difference equation x n +1 = ~ i =0 k f i x n m i p i , n =0,1,2,..., where k is a positive integer, f i , p i ] (0, X ) for i =0,..., k , and the initial conditions x m k , x m k +1 ,..., x 0 are arbitrary positive numbers.     

i．i．d随机变量随机和的数字特征

讨论了i．i．d的随机变量随机和的数学期望和方差、特征函数以及矩母函数的计算公式。并对求和个数服从几何分布和Possion分布，随机变量服从指数分布时给出了直接结果．     

Helicoidal surfaces in the three-dimensional Lorentz�CMinkowski space satisfying �� II r i ?=?�� i r i

In this paper, we study helicoidal surfaces without parabolic points in the 3-dimensional Lorentz?CMinkowski space under the condition ?? ^II r _i ?=??? _i r _i where ?? ^II is the Laplace operator with respect to the second fundamental form and ?? _i is a real number. We prove that there are no helicoidal surfaces without parabolic points in the 3-dimensional Lorentz?CMinkowski space satisfying that condition.     

Factorable surfaces in the three-dimensional Euclidean and Lorentzian spaces satisfying Δr i ?=?λ i r i

In this paper we classify the factorable surfaces in the three-dimensional Euclidean space ${\mathbb{E}^{3}}$ and Lorentzian ${\mathbb{E}_{1}^{3}}$ under the condition ??r _i ?=??? _i r _i , where ${\lambda_{i}\in\mathbb{R}}$ and ?? denotes the Laplace operator and we obtain the complete classification for those ones.     

尤拉公式e~(θi)=cosθ+i sin θ

引言在这篇短文里,我們向讀者介紹一种新的建立尤拉公式的方法。我們不用一般数学分析里所用的方法,而用一个人家熟知的重要极限来建立尤拉公式。同时,我們考虑到尤拉公式的应用很广泛,也很重要,因此,順便列举了一些应用。其中特别請大家注意应用4和5,显然这样做是不够严格的,但我們想借此向讀者說明:当在复数城里研究初等函数时会出現实数城里沒有的有趣性质,从而帮助我們更深地理解初等实函数。这对中学数学教师是有帮助的。§1.尤拉公式e~(θi)=cosθ+isinθ的推导在数学分析里已經証明了一个重要极限 e~θ=(?)(1+θ/n)~n,这里θ为任意实数。推广这个結果于θi,得 e~(θi)=(?)(1+θi/n)~n (1)这里θ为任意实数,而i为虚数单位。現在我們来計     

(i1i)*(b12k0)及(i1i)*(b31k0)在π*V(1)中的收敛性

对连通有限型谱X,y,存在Adams谱序列{Es,tr,dr},满足(1)dr:Es,t,r→Es+r,t+r-1,r是谱序列的微分, (2)Es,t,2≌Exts,t,A(H*X,H*y),(3)收敛到[∑t-sY,X].当X分别是球谱S,Moore谱M,Toda-smith谱V(1)时,(πt-X)p分别是S,M,V(1)的稳定同伦群.利用Adams 谱序列,证明了(i1i)*(62,1k0)及(i1i)*(b3,1k0)是永久循环但不是边缘,因此收敛到π*V(1)中的非零元,其中P为奇索数,q=2p-2.     

Percolation in invariant Poisson graphs with?i.i.d.?degrees

Let each point of a homogeneous Poisson process in ℝ ^d independently be equipped with a random number of stubs (half-edges) according to a given probability distribution μ on the positive integers. We consider translation-invariant schemes for perfectly matching the stubs to obtain a simple graph with degree distribution μ. Leaving aside degenerate cases, we prove that for any μ there exist schemes that give only finite components as well as schemes that give infinite components. For a particular matching scheme which is a natural extension of Gale–Shapley stable marriage, we give sufficient conditions on μ for the absence and presence of infinite components.     

On Euler's Formula exp (iθ) = cosθ + i sinθ

In approximating a function with a pole‐like singularity at a non‐rational point a* by a rational polynomial, the approximating package will be robust (i.e. undetectably erroneous to a user) if the rational polynomial includes a factor which cancels out the pole to the full accuracy of the machine in use. Naturally in order to be portable, the approximation a to a* must be to the full machine accuracy of the receiving machine.     

关于图Kn-H2n+i(i=1,2)的升分解

Yousef.Alavi等人在文献[1]中定义了一种新分解(Ascending Subgraph Decomposition),即"升分解",并且猜想:任意有正整数条边的图都可以升分解.本文证明了下面两个结论:1. Kn-H2n+1可以升分解,其中H2n+1为含有2n+1条边的Kn的子图;2. Kn-H2n+2可以升分解,其中H2n+2为含有2n+2条边的Kn的子图.     

Computing Proximal Points of Convex Functions with Inexact Subgradients

Locating proximal points is a component of numerous minimization algorithms. This work focuses on developing a method to find the proximal point of a convex function at a point, given an inexact oracle. Our method assumes that exact function values are at hand, but exact subgradients are either not available or not useful. We use approximate subgradients to build a model of the objective function, and prove that the method converges to the true prox-point within acceptable tolerance. The subgradient g _k used at each step k is such that the distance from g _k to the true subdifferential of the objective function at the current iteration point is bounded by some fixed ε > 0. The algorithm includes a novel tilt-correct step applied to the approximate subgradient.     

Incremental proximal methods for large scale convex optimization

We consider the minimization of a sum \({\sum_{i=1}^mf_i(x)}\) consisting of a large number of convex component functions f _i . For this problem, incremental methods consisting of gradient or subgradient iterations applied to single components have proved very effective. We propose new incremental methods, consisting of proximal iterations applied to single components, as well as combinations of gradient, subgradient, and proximal iterations. We provide a convergence and rate of convergence analysis of a variety of such methods, including some that involve randomization in the selection of components. We also discuss applications in a few contexts, including signal processing and inference/machine learning.     

On Ochoa's special matrices in matrix classes

It is well known that the ideal classes of an order Z[μ], generated over Z by the integral algebraic number μ, are in a bijective correspondence with certain matrix classes, that is, classes of unimodularly equivalent matrices with rational integer coefficients. If the degree of μ is ?3, we construct explicitly a particularly simple ideal matrix for an ideal which is a product of different prime ideals of degree 1. We obtain the following special n×n matrix (c_ij) in the matrix class corresponding to the ideal class of our ideal: c_i+1,_i=1(i=1,…,n?2); c_ij=0(?i?n, 1?j?n? 2, and i≠j+1); c_nj=0(j)=2,…,n?1). The remaining coefficients are given as explicit polynomials in an integer z which depends on the ideal. It is shown that the matrix class of every regular ideal class of Z[μ] contains a special matrix of this kind.     

Continuously decreasing solutions for polynomial-like iterative equations

Most known results on existence,uniqueness and stability for solutions of the polynomial-like iterative equation Σni=1λifi(x)=F(x) were obtained in the case of λ 1 = 0.In this paper,we construct C 0 decreasing solutions of the iterative equation in the case that λ 1 can vanish to answer the Leading Coefficient Problem.Moreover,we also give the necessary and sufficiently condition for uniqueness of solutions.     

Point estimation for multi-spectral distributed random matrices

In this communication, we consider a p×n random matrix which is normally distributed with mean matrix M and covariance matrix Σ, where the multivariate observation x_i=y_i+?_i with p dimensions on an object consists of two components, the signal y_i with mean vector μ and covariance matrix Σ_s and noise with mean vector zero and covariance matrix Σ_?, then the covariance matrix of x_i and x_j is given by Σ=Cov(x_i,x_j)=Γ⊗(B_|i-j|Σ_s+C_|i-j|Σ_?), where Γ is a correlation matrix; B_|i-j| and C_|i-j| are diagonal constant matrices. The statistical objective is to consider the maximum likelihood estimate of the mean matrix M and various components of the covariance matrix Σ as well as their statistical properties, that is the point estimates of Σ_s,Σ_? and Γ. More importantly, some properties of these estimators are investigated in slightly more general models.     

Reducing the bandwidth of a sparse matrix with tabu search

The bandwidth of a matrix A={a_ij} is defined as the maximum absolute difference between i and j for which a_ij≠0. The problem of reducing the bandwidth of a matrix consists of finding a permutation of the rows and columns that keeps the nonzero elements in a band that is as close as possible to the main diagonal of the matrix. This NP-complete problem can also be formulated as a labeling of vertices on a graph, where edges are the nonzero elements of the corresponding symmetrical matrix. Many bandwidth reduction algorithms have been developed since the 1960s and applied to structural engineering, fluid dynamics and network analysis. For the most part, these procedures do not incorporate metaheuristic elements, which is one of the main goals of our current development. Another equally important goal is to design and test a special type of candidate list strategy and a move mechanism to be embedded in a tabu search procedure for the bandwidth reduction problem. This candidate list strategy accelerates the selection of a move in the neighborhood of the current solution in any given iteration. Our extensive experimentation shows that the proposed procedure outperforms the best-known algorithms in terms of solution quality consuming a reasonable computational effort.     

On distance-regularity in graphs

If A is the adjacency matrix of a graph G, then A_i is the adjacency matrix of the graph on the same vertex set in which a pair of vertices is adjacent if and only if their distance apart is i in G. If G is distance-regular, then A_i is a polynomial of degree i in A. It is shown that the converse is also true. If A_i is a polynomial in A, not necessarily of degree i, G is said to be distance-polynomial. It is shown that this is a larger class of graphs and some of its properties are investigated.     

On the uniqueness of overcomplete dictionaries, and a practical way to retrieve them

A full-rank under-determined linear system of equations Ax = b has in general infinitely many possible solutions. In recent years there is a growing interest in the sparsest solution of this equation—the one with the fewest non-zero entries, measured by ∥x∥₀. Such solutions find applications in signal and image processing, where the topic is typically referred to as “sparse representation”. Considering the columns of A as atoms of a dictionary, it is assumed that a given signal b is a linear composition of few such atoms. Recent work established that if the desired solution x is sparse enough, uniqueness of such a result is guaranteed. Also, pursuit algorithms, approximation solvers for the above problem, are guaranteed to succeed in finding this solution.Armed with these recent results, the problem can be reversed, and formed as an implied matrix factorization problem: Given a set of vectors {b_i}, known to emerge from such sparse constructions, Ax_i = b_i, with sufficiently sparse representations x_i, we seek the matrix A. In this paper we present both theoretical and algorithmic studies of this problem. We establish the uniqueness of the dictionary A, depending on the quantity and nature of the set {b_i}, and the sparsity of {x_i}. We also describe a recently developed algorithm, the K-SVD, that practically find the matrix A, in a manner similar to the K-Means algorithm. Finally, we demonstrate this algorithm on several stylized applications in image processing.     

Estimation of states and parameters in continuous non-linear systems with discrete observations

We consider a class of continuous non-linear systems defined by the ordinary differential equation x = f(x, t) + g(x, t)u, where u is an unknown input representing noise or disturbances. The object is to estimate states and parameters in these systems by means of a fixed number of discrete observations y_i = h(x(t_i), t_i) + v_i, 1 ? i ? m, where the v_i represents unknown errors in the measurements y_i. No statistical assumptions are made concerning the nature of the unknown input u or the unknown measurement errors v_i. A weighted least squares criterion is defined as a measure of the optimal estimate. A result concerning the existence of solutions of the differential equation which minimize the criterion is presented. The necessary conditions for an optimal estimate, a set of Euler-Lagrange equations and multi-point discontinuous non-linear boundary conditions, are given. The multi-point problem is converted to an equivalent continuous two-point boundary value problem of larger dimension in the case in which the observations are assumed to be linear functions of the state. A pair of equivalent quasilinearization algorithms is defined for the two-point system and the multi-point system. Quadratic convergence for these algorithms is proved.     

The asymptotic distribution of a goodness of fit statistic for factorial invariance

Suppose that random factor models with k factors are assumed to hold for m, p-variate populations. A model for factorial invariance has been proposed wherein the covariance or correlation matrices can be written as Σ_i = LC_iL′ + σ_i²I, where C_i is the covariance matrix of factor variables and L is a common factor loading matrix, i = 1,…, m. Also a goodness of fit statistic has been proposed for this model. The asymptotic distribution of this statistic is shown to be that of a quadratic form in normal variables. An approximation to this distribution is given and thus a test for goodness of fit is derived. The problem of dimension is considered and a numerical example is given to illustrate the results.