单A直和子空间

引入单直和子空间的概念,证明了线性空间可唯一分解为单直和子空间的直和,并且给出了计算方法.     

Reducing Agents for Improving the Stability of Sn‐based Perovskite Solar Cells

Organic‐inorganic hybrid perovskite solar cells (PSCs) have aroused tremendous research interest for their high efficiency, low cost and solution processability. However, the involvement of toxic lead in state‐of‐art perovskites hinders their market prospects. As an alternative, Sn‐based perovskites exhibit similar semiconductor characteristics and can potentially achieve comparable photovoltaic performance in comparison with their lead‐based counterparts. The main challenge of developing Sn‐based PCSs lies in the intrinsic poor stability of Sn²⁺, which could be oxidized and converted to Sn⁴⁺. Notably, introduction of SnX₂ (X=Cl, Br, I) additive becomes indispensable in the fabrication process, which highlights the importance of incorporating a reducing agent to improve the device stability. Additionally, efforts are made to utilize other reducing agents with different functions for the further enhancement of device performance. Currently, Sn‐based PSCs could attain a record efficiency over 10% with great stability. In this review, we present the recent progress on reducing agents for improving the stability of Sn‐based PSCs, and we hope to shed light on the challenges and opportunities of this research field.     

Improvement of the recursive projection method for linear iterative scheme stabilization based on an approximate eigenvalue problem

An algorithm for stabilizing linear iterative schemes is developed in this study. The recursive projection method is applied in order to stabilize divergent numerical algorithms. A criterion for selecting the divergent subspace of the iteration matrix with an approximate eigenvalue problem is introduced. The performance of the present algorithm is investigated in terms of storage requirements and CPU costs and is compared to the original Krylov criterion. Theoretical results on the divergent subspace selection accuracy are established. The method is then applied to the resolution of the linear advection–diffusion equation and to a sensitivity analysis for a turbulent transonic flow in the context of aerodynamic shape optimization. Numerical experiments demonstrate better robustness and faster convergence properties of the stabilization algorithm with the new criterion based on the approximate eigenvalue problem. This criterion requires only slight additional operations and memory which vanish in the limit of large linear systems.     

Majorization in de Branges spaces I. Representability of subspaces

In this series of papers we study subspaces of de Branges spaces of entire functions which are generated by majorization on subsets D of the closed upper half-plane. The present, first, part is addressed to the question which subspaces of a given de Branges space can be represented by means of majorization. Results depend on the set D where majorization is permitted. Significantly different situations are encountered when D is close to the real axis or accumulates to i∞.     

On the asymptotic number of inequivalent binary self-dual codes

Let Ψn be the number of inequivalent self-dual codes in . We prove that , where . Let Δn be the number of inequivalent doubly even self-dual codes in . We also prove that .     

用于光谱解混的正交向量投影算法

光谱解混是高光谱技术中的关键部分,对地物成分的定量分析至关重要。线性光谱解混方法在计算端元丰度时,大多需要涉及矩阵求逆或方阵行列式的计算,导致软件实现的计算复杂度高,且硬件实现困难。同时,当端元数量增加时,算法的计算量也会随之呈指数级快速增长。论文基于传统的正交子空间投影方法,利用正交原理,提出了一种新的光谱解混方法——正交向量投影。该方法首先利用Gram-Schmidt过程计算每个端元的最终正交向量分量,并将其作为代表端元的投影向量。然后对于任意的待解混光谱向量,直接将其投影到该正交向量上。最后,计算得到投影分量的长度与正交向量的长度比,即为该正交向量所代表端元的无约束丰度。该过程避免了正交子空间投影和最小方差方法中计算复杂、实现困难的矩阵求逆运算,更便于并行计算的设计和硬件实现。通过理论的推导分析,证明了该算法与正交子空间投影和最小方差方法是完全一致的。另外,由于算法避免了矩阵相乘和求逆运算,简化了解混过程,通过对不同算法复杂度的具体分析,也证明该算法相对其他算法可以对端元数量降低一个量级。最后,在模拟数据和实际图像上分别进行实验测试,结果的分析和比较,也说明了算法的有效性。     

Aliasing Error of Sampling Series in Wavelet Subspaces

Alising error arises whenever a sampling formula, valid for a prescribed space, is applied to a function in a bigger space. In this work, we estimate the aliasing error of classic and average sampling expansions in wavelet subspaces of a multiresolution analysis.     

Recursion relations for the extended Krylov subspace method

The evaluation of matrix functions of the form f(A)v, where A is a large sparse or structured symmetric matrix, f is a nonlinear function, and v is a vector, is frequently subdivided into two steps: first an orthonormal basis of an extended Krylov subspace of fairly small dimension is determined, and then a projection onto this subspace is evaluated by a method designed for small problems. This paper derives short recursion relations for orthonormal bases of extended Krylov subspaces of the type K^m,mi+1(A)=span{A^-m+1v,…,A^-1v,v,Av,…,A^miv}, m=1,2,3,…, with i a positive integer, and describes applications to the evaluation of matrix functions and the computation of rational Gauss quadrature rules.     

Shift‐invert Lanczos method for the symmetric positive semidefinite Toeplitz matrix exponential

The Lanczos method with shift‐invert technique is exploited to approximate the symmetric positive semidefinite Toeplitz matrix exponential. The complexity is lowered by the Gohberg–Semencul formula and the fast Fourier transform. Application to the numerical solution of an integral equation is studied. Numerical experiments are carried out to demonstrate the effectiveness of the proposed method. Copyright © 2010 John Wiley & Sons, Ltd.     

BiCGstab(l) and other hybrid Bi-CG methods

It is well-known that Bi-CG can be adapted so that the operations withA ^T can be avoided, and hybrid methods can be constructed in which it is attempted to further improve the convergence behaviour. Examples of this are CGS, Bi-CGSTAB, and the more general BiCGstab(l) method. In this paper it is shown that BiCGstab(l) can be implemented in different ways. Each of the suggested approaches has its own advantages and disadvantages. Our implementations allow for combinations of Bi-CG with arbitrary polynomial methods. The choice for a specific implementation can also be made for reasons of numerical stability. This aspect receives much attention. Various effects have been illustrated by numerical examples.