分数次积分变换的交换子在齐型空间上的端点估计

令T为P^n上的Caldero＇n-Zygmund积分算子,由T构成的交换子的有界性已有较完善的结论,本文的目的是将之推广到一般的齐型空间。设（X,d,μ）为齐型空间,将引进齐型空间（X,d,μ）上的分数次积分变换构成的交换子Iγ^b,并证明分数次积分变换构成的交换子Iγ^b的端点估计,即砖是从L^1/γ（X）到BMO（X）有界的,从Bp^γ（X）到CMO（X）有界的。     

基于二维图像矩阵的ICA人脸识别

为了解决传统独立分量分析(ICA)在人脸识别过程中存在的高维小样本问题,同时为了提高识别效率,提出了一种基于二维图像矩阵的独立分量分析(ICA)特征提取方法.该方法将人脸图像矩阵作为训练样本,首先利用主分量分析(PCA)对训练样本进行去二阶相关和降维处理,然后对处理后的样本进行ICA特征提取,由于训练样本维数很小,因此它降低了传统ICA方法中高维小样本问题产生的识别错误率,同时减少了识别时间.在Yale人脸库和ORL人脸库上验证了该算法的有效性.     

基于改进的Capon滤波器组谱估计新方法

为了解决Capon滤波器组谱估计方法在α稳定分布噪声下性能出现退化的问题,提出了一种改进的Capon滤波器组谱估计方法,利用分数低阶协方差(FLOC)对传统的Capon滤波器组进行重构.由于分数低阶协方差的作用范围是0＜α≤2整个分数低阶空间,因此在α稳定分布噪声下其谱估计性能比基于二阶统计量方法的谱估计性能更好.计算机仿真结果显示了这种方法的优越性能,并且在高斯噪声环境下,其性能与二阶统计量下的方法类似.     

大型动力系统的降维：基于模态截断的非线性Galerkin方法

为了有效地求解大型动力系统,现已提出了各种降维方法．根据非线性Galerkin方法的求解思路,我们将大型动力系统分解成三个子系统,即”慢子系统”、”适速子系统”和”快子系统”．在此基础上提出了改进的非线性Galerkin方法,即：在数值积分过程中将适速子系统的贡献导入慢子系统．然后,以一个含有立方非线性的5自由度强迫振动系统为例阐明了新方法的有效性．     

融合指标分组的高维混合多目标进化优化

高维混合多目标优化问题因包含多个不同类型指标,目前尚缺乏有效求解该问题的进化优化方法。提出一种基于目标分组的高维混合多目标并行进化优化方法。采用深度学习神经网络预测种群隐式性能指标;基于指标相关性,将高维混合多目标优化问题分解为若干子优化问题;采用多种群并行进化算法,求解分解后的每一子优化问题,并基于各子种群的非被占优解构建外部保存集;采用聚合函数对外部保存集个体进一步优化,得到Pareto最优解集。在室内布局优化问题中验证所提方法,实验结果表明,所提方法的Pareto最优解在收敛性、分布性以及延展性等方面均优于对比方法。     

Riemann-Liouville型分数阶导数的非线性估计（英文）

本文主要研究任意有界连续信号的Riemann-Liouville分数阶导数估计问题.当分数阶α属于0到1时,首先利用滑模技术提出一种有界连续信号分数阶导数的非线性估计方法;然后将其结果推广至分数阶α∈R⁺的情况,并给出相应的非线性估计方案.借助Riemann-Liouville分数阶微积分频率分布模型,本文详细分析讨论了所给分数阶导数非线性估计的收敛性问题,并得到相应闭环系统是渐近稳定的结论.文中所提方法的主要优点是在事先未知给定信号分数阶导数上界的情况下,不仅能自适应地估计其Riemann-Liouville分数阶导数,而且当信号中含有随机噪声和不确定扰动时依然能正常工作.数值仿真实例验证了本文所给估计方法的可行性和有效性.     

分数阶时滞非线性多智能体系统的自适应控制

针对分数阶多智能体系统中存在时滞和非线性特性, 时滞往往会引起控制系统的性能下降甚至出现系统 不稳定等问题, 提出了一种含时滞非线性的分数阶多智能体系统自适应控制方法. 对于多智能体系统的控制协议, 设计了基于领导者和相邻智能体状态信息的自适应控制协议, 减小了过大常数控制增益带来的能源浪费. 对于一 致性, 利用图论基础、分数阶Halanay不等式稳定性定理、Kronecker积和Schur补引理, 获得了分数阶时滞非线性多 智能体系统的LMI一致性条件. 仿真结果验证了本文算法的正确性和有效性. 由于整数阶系统是分数阶系统的特殊 形式, 本文结论可以直接推广到整数阶多智能体系统中.     

The transient response of a functionally graded piezoelectric rod subjected to a moving heat source under fractional order theory of thermoelasticity

The transient thermo-piezoelectric response of a functionally graded piezoelectric rod subjected to a moving heat source is investigated in the context of fractional order theory of thermoelasticity proposed by Sherief. The material properties of the functionally graded piezoelectric rod are assumed to vary exponentially along the length, except for the thermal relaxation time and the specific heat, which are taken to be constant. To solve the governing equations of the problem, Laplace transform is applied, eliminating the time effect; the analytical solutions of the displacement, stress, temperature, and electric field in Laplace domain are obtained. Subsequently, the solutions of the considered variables in time domain are obtained by numerical Laplace inversion and illustrated graphically. In calculation, the effect of the fractional order parameter on the variations of the considered variables is presented.     

Probabilistic crack trajectory analysis by a dimension reduction method

This paper proposes a novel analysis method of stochastic crack trajectory based on a dimension reduction approach. The developed method allows efficiently estimating the statistical moments, probability density function and cumulative distribution function of the crack trajectory for cracked elastic structures considering the randomness of the loads, material properties and crack geometries. First, the traditional dimension reduction method is extended to calculate the first four moments of the crack trajectory, in which the responses are eigenvectors rather than scalars. Then the probability density function and cumulative distribution function of the crack trajectory can be obtained using the maximum entropy principle constrained by the calculated moments. Finally, the simulation of the crack propagation paths is realized by using the scaled boundary finite element method. The proposed method is well validated by four numerical examples performed on varied cracked structures. It is demonstrated that this method outperforms the Monte Carlo simulation in terms of computational efficiency, and in the meanwhile, it has an acceptable computational accuracy.     

Minimum Setup Minimum Aberration Two‐level Split‐plot Type Designs for Physical Prototype Testing

Although new technologies allow for less effort in prototyping, physical testing still remains an important step in the product development cycle. Well‐planned experiments are useful to guide the decision‐making process. During the design of an experiment, one of the challenges is to balance limited resources and system constraints to obtain useful information. It is common that prototypes are composed of several parts, with some parts more difficult to assemble than others. And, usually, there is only one piece available of each part type and a large number of different setups. Under these conditions, designs with randomization restrictions become attractive approaches. Considering this scenario, a new and additional criterion, minimum setup, to construct split‐plot type designs is presented. Designs with the minimum number of setups of the more difficult parts, which are especially useful for screening purposes in physical prototype testing, are discussed. The use of the proposed criterion combined with minimum aberration for selecting a regular design is shown through a real application in testing car prototypes. As a tool to practitioners, catalogs of selected 32‐run minimum setup minimum aberration split‐split‐plot and split‐split‐split‐plot designs are presented. More complete catalogs are available as Supporting information. Copyright © 2015 John Wiley & Sons, Ltd.