Nonparametric estimation and adaptive control in a class of finite Markov decision chains

We consider a class of Markov decision processes withfinite state and action spaces which, essentially, is determined by the following condition: The state space isirreducible under the action of any stationary policy. However, except by this restriction, the transition law iscompletely unknown to the controller. In this context, we find a set of policies under which thefrequency estimators of the transition law are strongly consistent and then, this result is applied to constructadaptive asymptotically discount-optimal policies.Dedicated to Professor Truman O. Lewis, on the occasion of his sixtieth birthdayThis research was supported in part by the Third World Academy of Sciences (TWAS) under Grant TWAS RG MP 898-152, and in part by the Consejo Nacional de Ciencia y Tecnología (CONACYT) under Grant A128CCOEO550 (MT-2).     

The Tikhonov regularization method in elastoplasticity

The numerical simulation of the mechanical behavior of industrial materials is widely used for viability verification, improvement and optimization of designs. Elastoplastic models have been used to forecast the mechanical behavior of different materials. The numerical solution of most elastoplastic models comes across problems of ill-condition matrices. A complete representation of the nonlinear behavior of such structures involves the nonlinear equilibrium path of the body and handling of singular (limit) points and/or bifurcation points. Several techniques to solve numerical problems associated to these points have been disposed in the specialized literature. Two examples are the load-controlled Newton–Raphson method and displacement controlled techniques. However, most of these methods fail due to convergence problems (ill-conditioning) in the neighborhood of limit points, specially when the structure presents snap-through or snap-back equilibrium paths. This study presents the main ideas and formalities of the Tikhonov regularization method and shows how this method can be used in the analysis of dynamic elastoplasticity problems. The study presents a rigorous mathematical demonstration of existence and uniqueness of the solution of well-posed dynamic elastoplasticity problems. The numerical solution of dynamic elastoplasticity problems using Tikhonov regularization is presented in this paper. The Galerkin method is used in this formulation. Effectiveness of Tikhonov’s approach in the regularization of the solution of elastoplasticity problems is demonstrated by means of some simple numerical examples.     

一类非线性边值问题的近似解

运用修正迭代法求出一系列无量纲的特征关系曲线,研究解决非线性本质的积液问题     

关于广义鞍点问题的HSS迭代方法的收缩因子(英文)

白中治等提出了解非埃尔米特正定线性方程组的埃尔米特和反埃尔米特分裂(HSS)迭代方法(Bai Z Z,Golub G H,Ng M K.Hermitian and skew-Hermitian splitting methodsfor non-Hermitian positive definite linear systems.SIAM J.Matrix Anal.Appl.,2003,24:603-626).本文精确地估计了用HSS迭代方法求解广义鞍点问题时在加权2-范数和2-范数下的收缩因子.在实际的计算中,正是这些收缩因子而不是迭代矩阵的谱半径,本质上控制着HSS迭代方法的实际收敛速度.根据文中的分析,求解广义鞍点问题的HSS迭代方法的收缩因子在加权2-范数下等于1,在2-范数下它会大于等于1,而在某种适当选取的范数之下,它则会小于1.最后,用数值算例说明了理论结果的正确性.     

用广义变分迭代理论求一类相对转动动力学方程的解

研究了一类具有非线性阻尼力和强迫周期力项的相对转动扰动动力学方程. 首先利用变分原理构造了广义变分迭代, 其次决定方程的初始近似, 最后通过迭代表示式得到了对应方程的任意次近似解. 关键词： 相对转动 动力系统 变分迭代     

Iterative filtered ghost imaging

It is generally believed that, in ghost imaging, there has to be a compromise between resolution and visibility. Here we propose and demonstrate an iterative filtered ghost imaging scheme whereby a super-resolution image of a grayscale object is achieved, while at the same time the signal-to-noise ratio (SNR) and visibility are greatly improved, without adding complexity. The dependence of the SNR, visibility, and resolution on the number of iterations is also investigated and discussed. Moreover, with the use of compressed sensing the sampling number can be reduced to less than 1% of the Nyquist limit, while maintaining image quality with a resolution that can exceed the Rayleigh diffraction bound by more than a factor of 10.     

A RANDOM FIXED POINT ITERATION FOR THREE RANDOM OPERATORS ON UNIFORMLY CONVEX BANACH SPACES

In the present paper we introduce a random iteration scheme for three random operators defined on a closed and convex subset of a uniformly convex Banach space and prove its convergence to a common fixed point of three random operators. The result is also an extersion of a known theorem in the corresponding non-random case.     

再论求导数零点的二次收敛迭代法

一维搜索是最优化理论数值计算的一个基本问题,它可归结为求定义在开凸区域Ｄ上的可微函数 ｆ的导数零点．若用 Ｎｅｗｔｏｎ法求导数零点,则涉及到二阶导数的计算．若用带导数的三次插值法则需要开平方的计算［１］．为了克服上述问题,本文作者之一在 １９７９年［２］首次提出了下述具有二阶收敛速度的迭代法：通常,我们称迭代法（０．１）为基于信息集（ｆ（ｘｎ）,ｆ’（ｘｎ）,ｆ（ｘｎ－１）,ｆ’（ｘｎ－１）｝的迭代法,而δ（ｆｘｙ）是基于信息集｛ｆ（ｘ）,ｆ＇（ｘ）,ｆ（ｙ）,Ｆ＇（ｙ））｝的三次插值多项式在ｘ处…     

Phase imaging with rotating illumination

A modified extended-ptychographical-iterative-engine （ePIE） algorithm is proposed to overcome the dis- advantages of ePIE technique and reduce the influence of stage hysteresis or backlash error. The exit wave of a rotatable ＂screen＂ illuminated by plane wave is used as the illumination on the specimen, and the complex transmission functions of the rotatable object and specimen can be simultaneously reconstructed. Compared with the standard x - y scanning PIE algorithm, the proposed algorithm can completely avoid the influence of stage hysteresis （or backlash error）. The proposed algorithm also has higher convergence s!oeed and better accuracy than the standard PIE algorithm.     

解不适定算子方程的一个定常二步隐式迭代法

１．引言 设Ｘ,Ｙ是两个Ｈｉｌｂｅｒｔ空间,Ａ：Ｘ→Ｙ是有界线性算子,考虑算子方程 Ａｘ＝ｙ（１．１）如果Ａ的值域Ｒ（Ａ）在Ｙ中非闭,则方程（１．１）是不适定的［１］．许多应用科学中都归结出这一类方程,特别地,许多反问题是不适定的［２,３］．本文考虑方程（１．１）的 Ｍｏｏｒｅ－Ｐｅｎｒｏｓｅ广义解,这里Ａ是算子Ａ的Ｍｏｏｒｅ－Ｐｅｎｒｏｓｅ广义逆［１］．Ａ＋ｙ存在当且仅当本文均作这一假设．在实际中,通常代替（１．１）的是扰动方程这里右端项,为一给定的误差水平,Ｑ是Ｙ到Ｒ（Ａ）的正交投影算子．对扰…