Gamma mixture models for target recognition

This paper considers a mixture model approach to automatic target recognition using high-resolution radar measurements. The mixture model approach is motivated from several perspectives including requirements that the target classifier is robust to uncertainty in amplitude scaling, rotation and translation of the target. Estimation of the model parameters is achieved using the expectation-maximisation (EM) algorithm. Gamma mixtures are introduced and the re-estimation equations derived. The models are applied to the classification of high-resolution radar range profiles of ships and results compared with a previously published self-organising map approach.     

分布存储并行机上的自动数据布局优化模型

在分布式并行机上,数据布局的质量极大的影响着应用程序的执行性能,以往的研究一般将自动数据布局优化问题近似分解为数据对准优化和数据分布优化两步来解决,且对两者的结合只研究了一维的情况,在相关研究工作的基础上,在多维情况下将数据对准优化和数据分布优化结合在一个模型当中,提出了一个数据对准优化与数据分布优化统一的多维静态数据布局模型,避免了采用启发式策略,从而更加精确地描述了自动数据布局优化问题,同时给     

Estimation of the Bivariate Stable Spectral Representation by theProjection Method

A method of estimating the spectral representation of a generalized bivariatestable distribution is presented, based on a series of maximum likelihood (ML)estimates of the stable parameters of univariate projections of the data. Thecorresponding stable spectral density is obtained by solving a quadraticprogram. The proposed method avoids the often arduous task of computing themultivariate stable density, relying instead on the standard univariate stabledensity. The paper applies this projection procedure, under the simplifyingassumption of symmetry, to simulated data as well as to foreign exchangereturn data, with favorable results. Kanter projection coefficients governingconditional expectations are computed from the estimated spectral density. For the simulated data these compare well to their known true values.     

PDUIMS--基于持久存储的用户界面管理系统的设计与应用

用户界面作为软件系统的重要组成部分,在软件整个生命周期中具有独特的地位。软件质量控制的核心在于用户界面的有效、可扩展、高适应度的管理、常规的界面管理位于源码一级,对于大规模企业级应用将带来许多弊端文中介绍了一个利用动态加载和持久存储实现的面向商务处理的用户界面管理系统ＰＤＵＩＭＳ,该系统通过功能描述数据表存储用户界面实现了集中统一的数据库工程化界面管理和发布,对于应用语义提供了分离机制实例表明了该     

An Estimation of Complexity and Computational Costs for Vertical Block-Cyclic Distributed Parallel LU Factorization

The Vertical Block–cyclic Distributed Parallel LU Factorization Method (VBPLU) is effectively processed on a distributed memory parallel computer. VBPLU is based on the two techniques, the block algorithm and the aggregation of communications. Since startup time dominates the data communication and the aggregation reduces communication isssues, the total performance has been much improved. Furthermore this method uses long vectors so that it is also advantageous on vector processors. In this paper, we have constructed a modeling of VBPLU using a simplified LogGP model with analytical formulae, and estimated accurately the computational cost taking into account load distributions caused by data layout and process mapping. Some knowledge for optimization of block algorithm has been obtained. Our estimations have been verified through numerical experiments on three different distributed memory parallel computers.     

蒙特卡罗法及其在射弹散布仿真中的应用

作战仿真的真实性需要对抗双方火力射击效果的真实体现。文中提出了一种利用蒙特卡罗法进行射弹散布仿真的方法 ,并将结果与实际情况进行了比较。该方法已用于装甲兵数字化作战仿真实验室的作战仿真中     

BP神经网络在剩余油分布预测中的应用研究

我国多数油田经过一次、二次采油后,仅能采出地下总储量的30%左右,这意味着有60%～70%的剩余石油仍然残留在地下成为剩余油。加强剩余油分布规律研究、提高石油采收率不仅有着可观的经济效应,而且关系到国家石油战略的安全。本研究应用神经网络的原理,基于BP网络使用MATLAB语言建立一个剩余油分布的预测系统。该系统通过学习在地理坐标和孔隙度之间建立一个非线性函数关系,以此来预测任何区域的孔隙度,再通过孔隙度与剩余油饱和度之间的关系达到剩余油分布预测的目的。     

Efficient multitasking in a dual-core CPU system

The paper offers an associative-neural-net method to optimize resource allocation between independent tasks in a multiprocessor system. In the case of a dual-core CPU the method allows the task to be fully solved in O(M) operations. The text was submitted by the authors in English.     

主蒸汽母管压力自动控制及其实施方案

针对主蒸汽母管压力自动控制难以实现的问题,设计了一种独立的母管压力控制系统,规划了它与各台锅炉DCS之间的信息交换方案,提出了调压锅炉在线识别及蒸汽母管总负荷给定的计算方法;应用等微增率准则进行锅炉负荷的优化分配,得到一种能兼顾控制品质和机组经济性的母管压力自动控制方案。应用结果表明,该方案易于实现,且有很高的控制精度和很好的节煤效果。     

On basic properties of fault-tolerant multi-topology routing

Multi-topology routing has recently gained popularity as a simple yet efficient traffic engineering concept. Its basic purpose is to separate different classes of network traffic, which are then transported over disjoint logical topologies. Multi-topology routing is used as a basis for implementation of an IP fast reroute scheme called Multiple Routing Configurations (MRC).MRC has a range of attractive properties, but they do come at a cost. In order to guarantee recovery from any single link or node failure in the network, MRC has to maintain several logical topologies and thus an increased amount of routing information. The number of the logical topologies in MRC need not be large; even simple heuristic algorithms often yield good results in practice. However, why this is the case is not fully understood yet.In this paper, we introduce a theoretical framework for fault-tolerant multi-topology routing (FT-MTR). MRC is a practical implementation of FT-MTR in connectionless IP networks. We use FT-MTR to study how the internal topological structure of the communication network relates to two important problems. The first problem is minimizing the number of logical topologies and thus the routing state in FT-MTR. We show how to use the sets of nodes that separate the topology graph to devise an advanced heuristic for “intelligent” construction of the logical topologies. Finding the separating sets in a topology graph is computationally demanding; we present an algorithm that performs well in tested real network topologies. We evaluate the separation-set based heuristic for the logical topology construction and show that it outperforms the known MRC heuristics.The second problem is the FT-MTR load distribution after a failure. We use the separating sets to devise a novel algorithm for failure load distribution. This algorithm does not require knowledge of the traffic demand matrix, still, our tests indicate that it performs as good as, or better than, known MRC load-distribution algorithms that do require the demand matrix as input.