再生核移位勒让德基函数法求解分数阶微分方程

该文以再生核理论为基础,用移位Legendre多项式作为基函数构造了一个新的再生核空间,并给出了该空间下的再生核函数.与经典的再生核函数有所不同的是该空间下的再生核函数不再是分段函数,因此可以减小分数阶算子作用在核函数上时的计算量,使近似解更为精确.数值算例表明该方法的有效性.     

QMC Rules of Arbitrary High Order: Reproducing Kernel Hilbert Space Approach

In this paper we consider numerical integration of smooth functions lying in a particular reproducing kernel Hilbert space. We show that the worst-case error of numerical integration in this space converges at the optimal rate, up to some power of a log?N factor. A similar result is shown for the mean square worst-case error, where the bound for the latter is always better than the bound for the square worst-case error. Finally, bounds for integration errors of functions lying in the reproducing kernel Hilbert space are given. The paper concludes by illustrating the theory with numerical results.     

解二阶抛物型方程组的再生核函数法

建立了二阶抛物型方程组的一种新数值方法-再生核函数法.利用再生核函数,直接给出了每个离散时间层上近似解的显式表达式,由显式表达式可实现完全并行计算;用能量估计法证明了格式的稳定性及二阶收敛性;给出了一些数值结果.     

Existence Results for Fractional Order Semilinear Integro-Differential Evolution Equations with Infinite Delay

This paper is concerned with existence results of mild solutions for fractional order semilinear integro-differential evolution equations (FSIDEEs) and semilinear neutral integro-differential evolution equations (FSNIDEEs in short) with infinite delay in α-norm. Our tools include the Banach contraction principle, the nonlinear alternative of Leray–Schauder type and the Krasnoselskii–Schaefer type fixed point theorem.     

A Gradient Iteration Method for Functional Linear Regression in Reproducing Kernel Hilbert Spaces

We consider a gradient iteration algorithm for prediction of functional linear regression under the framework of reproducing kernel Hilbert spaces.In the algorithm, we use an early stopping technique, instead of the classical Tikhonov regularization, to prevent the iteration from an overfitting function.Under mild conditions, we obtain upper bounds, essentially matching the known minimax lower bounds, for excess prediction risk. An almost sure convergence is also established for the proposed alg...     

A Solution of an Infinite System of Quadratic Equations in Reproducing Kernel Space

We introduce several operators in certain reproducing kernel Hilbert spaces, and we use them in the solution of a general family of quadratic equations in an infinite number of variables. We further describe an approximation scheme with quadratic polynomials for solving these equations. Submitted: March 10, 2007. Revised: March 16, 2007. Accepted: April 10, 2007.     

On Reproducing Kernel Hilbert Spaces of Polynomials

Let (X,Y) be a minimal compactifiurtion of ?². In this paper, we determine the structure of such a (X,Y) in the case where X is a normal hypersurface of degree d ≤ 4 in P³.     

在再生核空间中求解非线性奇异两点边值问题

该文建立了一个迭代方法求解一类奇异两点边值问题(x_αu')'=f (x, u, u'), 其中x∈ (0,1),α< 2. 解的表达式是在再生核空间W₂[0,1]中以级数的形式给出的. 近似解一致收敛到准确解. 并且, 误差是单调下降的. 最后通过一些数值算例论述了所提方法的正确性与有效性.     

On the Reproducing Kernel Hilbert Spaces Associated with the Fractional and Bi-Fractional Brownian Motions

We present decompositions of various positive kernels as integrals or sums of positive kernels. Within this framework we study the reproducing kernel Hilbert spaces associated with the fractional and bi-fractional Brownian motions. As a tool, we define a new function of two complex variables, which is a natural generalization of the classical Gamma function for the setting we consider. D. Alpay thanks the Earl Katz family for endowing the chair which supports his research.     

Reproducing Kernel Hilbert Spaces and fractal interpolation

Reproducing Kernel Hilbert Spaces (RKHSs) are a very useful and powerful tool of functional analysis with application in many diverse paradigms, such as multivariate statistics and machine learning. Fractal interpolation, on the other hand, is a relatively recent technique that generalizes traditional interpolation through the introduction of self-similarity. In this work we show that the functional space of any family of (recurrent) fractal interpolation functions ((R)FIFs) constitutes an RKHS with a specific associated kernel function, thus, extending considerably the toolbox of known kernel functions and introducing fractals to the RKHS world. We also provide the means for the computation of the kernel function that corresponds to any specific fractal RKHS and give several examples.     

Symmetric Operators and Reproducing Kernel Hilbert Spaces

We establish the following sufficient operator-theoretic condition for a subspace S ì L² (\mathbbR, dn){S \subset L^2 (\mathbb{R}, d\nu)} to be a reproducing kernel Hilbert space with the Kramer sampling property. If the compression of the unitary group U(t) := e ^itM generated by the self-adjoint operator M, of multiplication by the independent variable, to S is a semigroup for t ≥ 0, if M has a densely defined, symmetric, simple and regular restriction to S, with deficiency indices (1, 1), and if ν belongs to a suitable large class of Borel measures, then S must be a reproducing kernel Hilbert space with the Kramer sampling property. Furthermore, there is an isometry which acts as multiplication by a measurable function which takes S onto a reproducing kernel Hilbert space of functions which are analytic in a region containing \mathbbR{\mathbb{R}} , and are meromorphic in \mathbbC{\mathbb{C}} . In the process of establishing this result, several new results on the spectra and spectral representations of symmetric operators are proven. It is further observed that there is a large class of de Branges functions E, for which the de Branges spaces H(E) ì L²(\mathbbR, |E(x)|^-2dx){\mathcal{H}(E) \subset L^{2}(\mathbb{R}, |E(x)|^{-2}dx)} are examples of subspaces satisfying the conditions of this result.     

分数阶脉冲中立型随机微积分方程的适定性

利用Sadovskii不动点定理以及α-预解算子理论讨论了一类在Hilbert空间中带无限时滞的分数阶脉冲中立型随机微积分方程温和解的适定性,并通过举例说明了结果的有效性.     

Legendre小波函数求解非线性Volterra积分微分方程组的数值解

Legendre小波函数被用于逼近非线性Volterra积分微分方程组的解,方法是基于Legendre小波的性质构建相应的积分算子矩阵,进而将原问题转化为关于未知解系数的线性方程组,通过求解该方程组,即得原问题的数值解.数值结果表明所述方法对于求解此类问题是行之有效的.     

A Method for Solving Initial Value Problems for Linear Differential Equations in Hilbert Space Based on The Cayley Transform

A first-order differential equation with a bounded operator coefficient in Hilbert space is considered. In case the coefficient is constant we establish a one-to-one correspondence between the continuous initial value problem and some discrete initial value problem. Using the Cayley transform we give explicit formulas for their solutions as well as formulas connecting corresponding continuous and discrete semigroups. On the basis of these formulas we propose a numerical algorithm for solving initial value problems with a bounded constant operator coefficient which has an exponential rate of convergence. If the operator coefficient is variable we use its piecewise constant approximation and the previously cited algorithm. Error estimates are given.     

基于组合神经网络的时间分数阶扩散方程计算方法

该文首次采用一种组合神经网络的方法，求解了一维时间分数阶扩散方程.组合神经网络是由径向基函数（RBF）神经网络与幂激励前向神经网络相结合所构造出的一种新型网络结构.首先，利用该网络结构构造出符合时间分数阶扩散方程条件的数值求解格式，同时设置误差函数，使原问题转化为求解误差函数极小值问题；然后，结合神经网络模型中的梯度下降学习算法进行循环迭代，从而获得神经网络的最优权值以及各项最优参数，最终得到问题的数值解.数值算例验证了该方法的可行性、有效性和数值精度.该文工作为时间分数阶扩散方程的求解开辟了一条新的途径.     

Sobolev-Type Fractional Stochastic Integrodifferential Equations with Nonlocal Conditions in Hilbert Space

We prove the existence of mild solution to Sobolev-type fractional stochastic integrodifferential equation with nonlocal conditions in Hilbert space. Also, we study the controllability of Sobolev-type fractional stochastic integrodifferential equations with impulsive conditions. We use uniformly continuous semigroups and fixed point technique for the main results. An example is provided to illustrate the theory.     

轴对称弹性动力学问题的重构核插值法

重构核插值法是近年来提出的一种新型无网格方法.该方法的形函数具有点插值性和高阶光滑性,不仅能够直接施加本质边界条件,而且能保证较高的计算精度.为了更有效地求解三维轴对称弹性动力学问题,对重构核插值法(reproducing kernel interpolation method, RKIM)应用于此类问题进行了研究,并发展了相应的数值模拟方法.由于几何形状和边界条件的轴对称性,计算时只需要横截面上离散节点的信息,因而前处理变得简单.采用Newmark-β法进行了时域积分.数值算例表明,轴对称弹性动力学分析的重构核插值法既有无网格方法的优势,又有较高的计算精度.     

Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces

Journal of Nonlinear Science - Transfer operators such as the Perron–Frobenius or Koopman operator play an important role in the global analysis of complex dynamical systems. The...     

关于边值问题的一种新的再生核数值算法

利用一种新的再生核算法讨论了二阶微分方程边值问题的数值解,并证明了解的收敛性.算法中,定义了再生核空间,避开了施密特正交化过程,借助于逆矩阵给出了近似解的表达式.通过数值算例,分析了数值解的逼近效果,并与泰勒级数法进行了比较,说明了方法的实用性和有效性.     

解带有Hilbert核的奇异积分方程的高精度组合算法

该文给出了用求积法解带Hilber核的奇异积分方程的高精度组合算法.把网格点分成互不相交的子集合, 在子集合上并行求解离散方程组, 再利用组合算法求得全局网格点的逼近.如果积分方程的系数属于B_δ, 则求积法的精度可达O(e^-nδ). 此外, 使用组合算法不仅能得到更高的精度阶, 而且能够得到后验误差估计. 数值算例的结果表明组合算法是极其有效的.