Duffing单边碰撞系统的混沌鞍合并激变

以典型的Duffing单边碰撞系统为研究对象,对系统中的混沌鞍进行了细致的分析.研究表明,系统的混沌鞍同样存在合并激变,合并激变是由连接两个混沌鞍的周期鞍的稳定流形与不稳定流形相切所诱发,相切使得边界上的混沌鞍与内部的混沌鞍发生碰撞而突然合并为一个较大的边界混沌鞍.混沌鞍的合并激变行为最终会诱导混沌吸引子的合并激变发生. 关键词： Duffing碰撞系统 混沌鞍 周期鞍 稳定与不稳定流形     

Long time behavior for nonlocal stochastic Kuramoto–Sivashinsky equations

In this paper, we consider a class of nonlocal stochastic Kuramoto–Sivashinsky equations driven by additive noises. Under some appropriate conditions, we investigate long time behavior, i.e., stability and growth bounds of the solutions to the equation. Finally, several examples are given to illustrate our results.     

Geometric and topological rigidity for compact submanifolds of odd dimension

We investigate rigidity problems for odd-dimensional compact submanifolds.We show that if Mn(n 5)is an odd-dimensional compact submanifold with parallel mean curvature in Sn+p,and if RicM(n-2-1n)(1+H2)and Hδn,whereδn is an explicit positive constant depending only on n,then M is a totally umbilical sphere.Here H is the mean curvature of M.Moreover,we prove that if Mn(n 5)is an odd-dimensional compact submanifold in the space form Fn+p(c)with c 0,and if RicM(n-2-εn)(c+H2),whereεn is an explicit positive constant depending only on n,then M is homeomorphic to a sphere.     

判定离散Hopfield神经网络稳定性的新方法

寻求判断离散Hofield神经网络稳定性的新判据。具体考虑神经元的权值矩阵元素和阀值之间的关系，依此判断能量函数的收敛性，得到了一个与阀值无关、不需权值矩阵对称的新判据；在新判据的基础上作出数学变形和分析，并用线性方程的解去刻划稳定点的存在性，得到了稳定点存在的一个充要条件。最后将离散Hopfield神经网络的稳定点存在问题转化为在有限区域内连续函数的零点解的问题。     

Length 3 complexes of abelian sheaves and Picard 2-stacks

We define a tricategory T[−2,0] of length 3 complexes of abelian sheaves, whose hom-bigroupoids consist of weak morphisms of such complexes. We also define a 3-category 2Pic(S) of Picard 2-stacks, whose hom-2-groupoids consist of additive 2-functors. We prove that these categories are triequivalent as tricategories. As a consequence we obtain a generalization of Deligne's analogous result about Picard stacks in SGA4, Exposé XVIII (Deligne (1973) [11]).     

拟线性回归预测模型的稳定最小二乘解

可线性化回归预测模型通过换元进行线性回归,换元前后的因变量具有异方差性,致使拟线性回归参数的精度较低.运用GL算法给出了此类模型的稳定最小二乘解,提高了参数的估计精度,最后给出了一个应用实例.     

A stable and accurate projection method on a locally refined staggered mesh

In this paper, a robust projection method on a locally refined mesh is proposed for two‐ and three‐dimensional viscous incompressible flows. The proposed method is robust not only when the interface between two meshes is located in a smooth flow region but also when the interface is located in a flow region with large gradients and/or strong unsteadiness. In numerical simulations, a locally refined mesh saves many grid points in regions of relatively small gradients compared with a uniform mesh. For efficiency and ease of implementation, we consider a two‐level blocked structure, for which both of the coarse and fine meshes are uniform Cartesian ones individually. Unfortunately, the introduction of the two‐level blocked mesh results in an important but difficult issue: coupling of the coarse and fine meshes. In this paper, by properly addressing the issue of the coupling, we propose a stable and accurate projection method on a locally refined staggered mesh for both two‐ and three‐dimensional viscous incompressible flows. The proposed projection method is based on two principles: the linear interpolation technique and the consistent discretization of both sides of the pressure Poisson equation. The proposed algorithm is straightforward owing to the linear interpolation technique, is stable and accurate, is easy to extend from two‐ to three‐dimensional flows, and is valid even when flows with large gradients cross the interface between the two meshes. The resulting pressure Poisson equation is non‐symmetric on a locally refined mesh. The numerical results for a series of exact solutions for 2D and 3D viscous incompressible flows verify the stability and accuracy of the proposed projection method. The method is also applied to some challenging problems, including turbulent flows around particles, flows induced by impulsively started/stopped particles, and flows induced by particles near solid walls, to test the stability and accuracy. Copyright © 2010 John Wiley & Sons, Ltd.     

Pattern memory analysis of second-order neural networks with time-delay

In this paper, the pattern memory of the second-order neural networks with time-delay are investigated based on the stability theory. Several sufficient conditions are obtained such that the equilibrium point is locally exponential stable when the equilibrium point located in the saturation region. These conditions can be directly derived from the synaptic connection weights and the external input of the second-order neural networks, and be verified easily. In addition, four examples are given to show the effectiveness of the results.     

JP3—1型示波极谱仪电源及显示系统的故障维修

本阐明了JP3—1型示波极谱仪电源及显示系统的工作原理，并举例说明这两部分的故障维修。