Properties of multilevel block -circulants

In a previous paper we characterized unilevel block α-circulants , , 0mn-1, in terms of the discrete Fourier transform of , defined by . We showed that most theoretical and computational problems concerning A can be conveniently studied in terms of corresponding problems concerning the Fourier coefficients F₀,F₁,…,F_n-1 individually. In this paper we show that analogous results hold for (k+1)-level matrices, where the first k levels have block circulant structure and the entries at the (k+1)-st level are unstructured rectangular matrices.     

Performance of a parallel algebraic multilevel preconditioner for stabilized finite element semiconductor device modeling

In this study results are presented for the large-scale parallel performance of an algebraic multilevel preconditioner for solution of the drift-diffusion model for semiconductor devices. The preconditioner is the key numerical procedure determining the robustness, efficiency and scalability of the fully-coupled Newton–Krylov based, nonlinear solution method that is employed for this system of equations. The coupled system is comprised of a source term dominated Poisson equation for the electric potential, and two convection–diffusion-reaction type equations for the electron and hole concentration. The governing PDEs are discretized in space by a stabilized finite element method. Solution of the discrete system is obtained through a fully-implicit time integrator, a fully-coupled Newton-based nonlinear solver, and a restarted GMRES Krylov linear system solver. The algebraic multilevel preconditioner is based on an aggressive coarsening graph partitioning of the nonzero block structure of the Jacobian matrix. Representative performance results are presented for various choices of multigrid V-cycles and W-cycles and parameter variations for smoothers based on incomplete factorizations. Parallel scalability results are presented for solution of up to 10⁸${10}^8$ unknowns on 4096 processors of a Cray XT3/4 and an IBM POWER eServer system.     

Approximation of high-dimensional kernel matrices by multilevel circulant matrices

Kernels are important in developing a variety of numerical methods, such as approximation, interpolation, neural networks, machine learning and meshless methods for solving engineering problems. A common problem of these kernel-based methods is to calculate inverses of kernel matrices generated by a kernel function and a set of points. Due to the denseness of these matrices, finding their inverses is computationally costly. To overcome this difficulty, we introduce in this paper an approximation of the kernel matrices by appropriate multilevel circulant matrices so that the fast Fourier transform can be applied to reduce the computational cost. Convergence analysis for the proposed approximation is established based on certain decay properties of the kernels.     

Optimization schemes for decomposition of fuzzy relations

The paper proposes an optimization environment for decomposing fuzzy relations. Two basic categories of approaches are developed: (i) based on direct gradient-oriented optimization methods, and (ii) exploiting the ideas of fuzzy neurocomputation. These two approaches are carefully analyzed and contrasted making use of illustrative numerical material. Some immediate applications to pattern classification and fuzzy interpolation are studied in detail. The study includes also some generalizations of the generic decomposition problem.     

多维区域上椭圆型方程Dirichlet问题的勒让德多小波多层扩充算法

用小波伽辽金方法求解多维区域上椭圆型方程齐次Dirichlet问题,构造了近似解空间的两个等价的勒让德多小波基,使得快速求解离散后的线性方程组的多层扩充算法得以实现.数值算例表明该算法是有效的.     

Reed-Muller codes and Barnes-Wall lattices: Generalized multilevel constructions and representation over GF(2<Superscript><Emphasis Type="Italic">q</Emphasis></Superscript>)

Generalized multilevel constructions for binary RM(r,m) codes using projections onto GF(2 ^q ) are presented. These constructions exploit component codes over GF(2), GF(4),..., GF(2 ^q ) that are based on shorter Reed-Muller codes and set partitioning using partition chains of length-2 ^l codes. Using these constructions we derive multilevel constructions for the Barnes-Wall Λ(r,m) family of lattices which also use component codes over GF(2), GF(4),..., GF(2 ^q ) and set partitioning based on partition chains of length-2 ^l lattices. These constructions of Reed-Muller codes and Barnes-Wall lattices are readily applicable for their efficient decoding.      

Are You Normal? The Problem of Confounded Residual Structures in Hierarchical Linear Models

We encounter hierarchical data structures in a wide range of applications. Regular linear models are extended by random effects to address correlation between observations in the same group. Inference for random effects is sensitive to distributional misspecifications of the model, making checks for (distributional) assumptions particularly important. The investigation of residual structures is complicated by the presence of different levels and corresponding dependencies. Ignoring these dependencies leads to erroneous conclusions using our familiar tools, such as Q–Q plots or normal tests. We first show the extent of the problem, then we introduce the fraction of confounding as a measure of the level of confounding in a model and finally introduce rotated random effects as a solution to assessing distributional model assumptions. This article has supplementary materials online.     

Obtaining confidence limits for safe creep life in the presence of multi batch hierarchical databases: An application to 18Cr–12Ni–Mo steel

The creep and creep rupture properties of 18Cr–12Ni–Mo steel tubes have been analysed using the Wilshire equations. The observed behaviour patterns are then briefly discussed in terms of the dislocation processes governing creep strain accumulation. A suitable statistical framework for analysing both the single and multi batch data available on this material is then specified. It is shown that ignoring the hierarchical nature present in many creep data bases, which has been the approach used until now when using the Wilshire equations, leads to a serious and significant underestimate of the predicted safe life for this material. The model allows accurate predictions, with associated levels of confidence, of long-term properties by extrapolation of short-term test results for this steel.     

修正的格子空间的密度泛函理论在狭缝中的应用

对描述单原子分子溶液在狭缝中的吸附现象的格子空间的密度泛函理论 (LDFT, lattice density functional theory)进行了修正, 在系统Helmholtz函数的推导中引入了平均场近似校正和Gibbs-Helmholtz方程. 对比Monte Carlo (MC)模拟结果, 发现LDFT理论对吸附分子在狭缝中的吸附浓度分布的预测与模拟数据有较大的偏差, 而修正模型的结果与模拟数据吻合较好 .随着体相浓度的变化,分子在狭缝中具有多级吸附行为, 具体表现为在特定体相浓度区, 对相同的体相浓度,狭缝中同时存在不同的分子浓度分布, 而在Gibbs等温线上可以明显看出多级吸附的性质. 对比修正前后的结果发现,两者均可以预测多级吸附行为, 但仍存在着较大的差异.     

Multilevel functional preconditioning for shape optimisation

We study the application of a multi-level preconditioner to a practical optimal shape design problem. The preconditioner is based on the Bramble-Pasciak-Xu (BPX) series. We extend it to the unstructured parametrization of 3D shapes by using the volume–agglomeration heuristics. The choice of the smoothing parameter is analysed from functional arguments. Application to the shape design for optimising aerodynamic and sonic boom performances of a wing is demonstrated.