Solving Multivariate Polynomial Matrix Diophantine Equations with Gr?bner Basis Method

Different from previous viewpoints, multivariate polynomial matrix Diophantine equations are studied from the perspective of modules in this paper, that is, regarding the columns of matrices as elements in modules. A necessary and sufficient condition of the existence for the solution of equations is derived. Using powerful features and theoretical foundation of Gr?bner bases for modules, the problem for determining and computing the solution of matrix Diophantine equations can be solved. Meanwh...     

An MPI+OpenACC-Based PRM Scalar Advection Scheme in the GRAPES Model over a Cluster with Multiple CPUs and GPUs

A moisture advection scheme is an essential module of a numerical weather/climate model representing the horizontal transport of water vapor. The Piecewise Rational Method(PRM) scalar advection scheme in the Global/Regional Assimilation and Prediction System(GRAPES) solves the moisture flux advection equation based on PRM. Computation of the scalar advection involves boundary exchange, and computation of higher bandwidth requirements is complicated and time-consuming in GRAPES. Recently, Graphic...     

离子推力器栅极组件热变形测量方法

栅极组件是离子推力器的核心部件,其所包含的多层栅极结构在工作过程中会发生热变形,导致栅极间距发生改变,进而影响离子推力器的工作性能及寿命。为了实现栅极结构在实际工况下热变形的非接触测量与评估,本研究提出了基于摄像测量的栅极变形观测方法,评价了不同图像分析方法（灰度重心法、圆拟合法、灰度匹配法）对变形测量精度的影响。结果表明灰度匹配方法观测精度高,环境适应性好;同时,设计并实现了一套栅极热变形环境模拟与变形测量系统,可实现高温、通水、通气环境下变形的高精度观测。最后,对环境箱通水通气对测量精度的影响进行了评价,结果表明二者均会对测量精度造成影响,通水对实验结果的影响大于通气的影响。     

含未知输入非线性系统的扩展平方根容积卡尔曼滤波算法

针对工程实际应用中存在的未知输入会导致经典的非线性滤波器状态估计精度下降甚至滤波发散的问题,提出了一种基于最小方差无偏估计(minimum variance unbiased estimation, MVUE)准则的扩展平方根容积卡尔曼滤波(extended square-root cubature Kalman filter, ESRCKF)算法。首先,结合上一时刻未知输入估计值对状态一步预测值进行修正,得到含未知输入条件下的状态预测值。其次,设计新息并采用加权最小二乘(weighted least squares, WLS)法获取当前时刻未知输入的无偏估计。最后,通过最小化协方差矩阵的迹,同时采用拉格朗日乘子法和舒尔补引理得到系统状态的最小方差无偏估计。仿真结果表明,相比于现有的非线性滤波算法,ESRCKF算法提高了在处理含未知输入非线性系统时的状态估计精度,并能同时实现系统状态和未知输入的最优估计,验证了该算法的有效性。     

基于时延嵌入式隐马尔科夫模型的癫痫脑电分类算法

癫痫脑电的分类识别能够为癫痫的预警和病程的发展监测提供强有力的技术支持。传统的癫痫脑电分类识别方法需要从较长的时间序列中提取特征,难以刻画大脑的瞬态变化,检测低效且耗时,降低了癫痫预警的有效性。针对上述问题,提出一种基于隐马尔科夫模型的癫痫脑电分类算法。该方法通过时延嵌入式隐马尔科夫模型(time-delay embedded hidden Markov model,TDE-HMM)对脑电进行状态估计,并提取状态序列中的状态切换特征,通过多层感知机(multiple layer perceptron,MLP)实现对不同癫痫发作阶段脑电的有效辨识。实验结果表明,相较于小波变换、微分熵等传统特征,所提方法准确率高,能够有效刻画癫痫不同阶段的大脑状态变化,为癫痫脑电的分类识别和状态分析提供了新的备选方案。     

喷涂角度对螺栓表面涂层厚度均匀性的影响

针对工程中采用铝涂料涂覆螺栓时螺栓表面铝涂层易出现的厚度不均匀问题,研究喷涂角度对螺栓表面涂层均匀性的影响规律。对喷涂系统的喷嘴和螺栓进行建模,通过计算流体动力学仿真软件Fluent建立了雾化流场的气液两相流物理模型,使用DPM模型分析了流场中气相和液相的相互作用,获得了在不同角度下的喷涂流场,预测了螺栓表面液膜沉积厚度。搭建了喷涂试验系统并与模拟结果进行了验证,模拟和试验研究均表明在喷涂角度为30°时螺栓表面涂层均匀性最佳。     

长潭水库大眼华鳊Sinibrama macrops年龄与生长的初步研究

大眼华鳊鳞片的年轮特征是以环片断裂间隙为主要特点的封闭○型轮纹。年轮形成时间一龄为4～5月,以后各龄相对推迟。体长与鳞长关系为L=37.42R+27.27(r=O.9445),体重与体长关系为W=0.01798L~(3.0518)(r=0.9674),体长生长方程为L_t=139.8[1-e~((-0.678)(t-0.3268))],体重生长方程为W_t=56.01[1-e~((-0.678(t-0.3268))]~3,其拐点坐标位置在t=1.95、W_(1.95)=16.64g,相当于0.297W_∞。大眼华鳊与鳙鱼存在摄食竞争,生长比鳙鱼慢,为了提高水库的渔业经济效益,宜适当控制大眼华鳊的种群数量。     

Novel cued search strategy based on information gain for phased array radar

A search strategy based on the maximal information gain principle is presented for the cued search of phased array radars. First, the method for the determination of the cued search region, arrangement of beam positions, and the calculation of the prior probability distribution of each beam position is discussed. And then, two search algorithms based on information gain are proposed using Shannon entropy and Kullback-Leibler entropy, respectively. With the proposed strategy, the information gain of each beam position is predicted before the radar detection, and the observation is made in the beam position with the maximal information gain. Compared with the conventional method of sequential search and confirm search, simulation results show that the proposed search strategy can distinctly improve the search performance and save radar time resources with the same given detection probability.     

Cluster Synchronization in a Complex Dynamical Network with Two Nonidentical Clusters

This paper further investigates cluster synchronization in a complex dynamical network with two-cluster. Each cluster contains a number of identical dynamical systems, however, the subsystems composing the two clusters can be different, i.e., the individual dynamical system in one cluster can differ from that in the other cluster. Complete synchronization within each cluster is possible only if each node from one cluster receives the same input from nodes in other cluster. In this case, the stability condition of one-cluster synchronization is known to contain two terms： the first accounts for the contribution of the inner-cluster coupling structure while the second is simply an extra linear term, which can be deduced by the ＂same-input＂ condition. Applying the connection graph stability method, the authors obtain an upper bound of input strength for one cluster if the first account is known, by which the synchronizability of cluster can be scaled. For different clusters, there are different upper bound of input strength by virtue of different dynamics and the corresponding cluster structure. Moreover, two illustrative examples are presented and the numerical simulations coincide with the theoretical analysis.     

要加强对复杂适应性系统的研究——对自组织理论的反思

简单回顾了自组织理论的发展历史、内容和采用的方法,重点分析了自组织理论的研究对象和研究范围;指出自组织理论在研究复杂系统上的局限性——只适于研究简单巨系统,它研究的是系统演化的结果而非过程;自组织理论使用微分方程作为数学工具,要求子系统之间的相互作用要满足叠加原理而不考虑涌现的情况。在此基础上,本文提出要加强复杂适应性系统的研究,具体有两方面的工作：首先要加强计算机作为数学工具的应用,扩展对系统状态描述的范围;另外要加强对层次性的研究,重点是对涌现问题的分析。最后提出现在加强复杂系统的研究应从实际的具体系统入手。