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Based on the traditional kinds of high-level synthesis of power-driven layout algorithm, this paper presents a new process of force-driven scheduling algorithm, in which the algorithm introduce a new data structure as an expression form of list scheduling, and improves the algorithm process.

在高层次综合中基于传统的力驱动布局算法提出一种新流程的力驱动调度算法,在该算法引进一种新的数据结构作为列表调度的表达形式,并改进了算法流程。

This paper describes the Atkin's elliptic curves primality proving algorithm and discusses all implementation details of this algorithm. Finally it gives the implemention of this algorithm by software and exhibits an example explicitly. This algorithm is implemented with software and this software is used to test some general large integers and acquire a good testing result.

文章给出了由Atkin提出的一种非常有效的素性测试方法即椭圆曲线素性证明算法,详细讨论了具体实施该算法的所有细节,而且通过在计算机上编程获得了其软件实现,并用该软件来测试一般的大整数的素性,取得了很好的效果。

ZhuWenyu implemented the above two algorithms on a PC, testing 3640471 with AKSalgorithm and 4295884871 with the first AKS-Bernstein algorithm in about 2478.94hours and 28.35 hours respectively. She concluded that it's almost impossible tojudge the primality of a given integer directly with AKS algorithm, and testifiedthat the first AKS-Bernstein algorithm improves the AKS algorithm, but it's notyet suitable for use in practice, either.

朱文余在微机同禧3206c/850上用C语言实现了AKS算法及上述改进,前一算法对3640471进行测试约需2478.94小时,而后者对4295884871进行测试约需28.35小时,从而指出在实际运用中直接利用AKS算法进行素性测定几乎不可能,而AKS-Bernstein第一算法比AKS算法有一些改进,但仍不实用。

First,we proposes the acceleration of Monte Carlo EM Algorithm,which is based on Monte Carlo EM Algorithm and Newton-Raphson algorithm,to improve the convergence rate;Second,the it is shown that the accelerated EM algorithm we proposed has quadratic convergence rate in a neighborhood of the posterior mode;Finally,its excellent performance in convergence rate is illustrated by a classical example.

受Monte Carlo EM算法与EM加速算法启发,本文构造了一种新的EM算法,称为Monte Carlo EM加速算法;证明了该算法在似然函数/后验分布的众数的附近确实具有二次收敛速度,改进了Monte Carlo EM算法的收敛速度;并通过一个数值例子的计算结果说明了该算法的优良性,它兼具实现简单及收敛速度快的特点。

We experimentally evaluate the effect of the proposed method using our emotion retrieval algorithm and random algorithm. Four kinds of emotion images, thick fashion images, succinct fashion images, passional scenery images and wide view scenery images are retrieved and compared. The experimental results show that our retrieval algorithm is better than random algorithm.

文中将本实验室实现的情感检索算法检索出的"厚重的"、"简洁的"服装图像以及"热情的"、"视野宽广的"风景图像与随机检索出的图像进行了比较,验证了基于心理量表的情感图像检索性能评价方法的有效性。

The simulation results show that this algorithm has better global convergence ability and more rapid convergence,and it is superior to Genetic Algorithm,Particle Swarm Optimization algorithm and QPSO algorithm.

仿真实例表明,该算法具有良好的全局收敛性能和快捷的收敛速度,调度效果优于遗传算法、粒子群优化算法和量子粒子群优化算法。

Dynamic programming algorithm was introduced to solve the problem. Based on discussion of calculation complexity and effectiveness, the exact DP Algorithm was successfully used in operative schedule of the collecting bucket in multi-car-single-layer mode, which has few service nodes. For problems with large number of service nodes, restricted DP algorithm was constructed to avoid rapid expand in calculation and memory demands during programming process. The restricted DP algorithm, successfully used in single-car-multilayer and compound service modes, gets balance between near optimal programming results and reasonable programming time, so as to meet the real time schedule demands.

文中首先在TSP-STW问题的动态规划模型基础上,论述了计算机精确动态规划解法的求解策略和方法以及算法的有效性和复杂性,并将其成功应用于服务节点数相对较少的多小车单层配药服务模式中集中料斗的集药动作规划;在进行服务节点数较多的单小车多层服务模式中取药小车的运动规划时,为限制计算量和存储空间需求的迅速膨胀,引入以合理限制动态规划算法在每一阶段保留的最大状态元素数为核心的有限动态规划法,以便在求解结果的优化程度和规划时间上取得均衡,达到实时调度的要求。

Based on the study of triangle mesh of creation algorithm, include the arithmetic of regular data make triangle mesh and irregular data make triangle mash. The paper put forward a optimized triangle mesh algorithm. Its key point is divide data into pieces in advance, then set up the net. The experiment result shows that this algorithm improves not only the efficiency of terrain molding, but also the precision compared with the old algorithms The main purposes of this paper are research visualization algorithm of three dimensions and the arithmetic of terrain visualization.

本文研究了基于三角形网格的地形建模的基本理论和方法,包括规则数据的三角网生成以及不规则三角网 TIN 的生成算法,总结了前人在这些方面所做的工作,本文提出了一种优化的三角网格生成算法,实验结果表明,该算法不仅提高了地形建模的效率,而且所生成的三角网格模型与以往算法相比精确性也有很大的提高。

Traditional link access control algorithm such as LBRCA(Link Bandwidth Require Control Algorithm) has the problem of high link access rejection probability and low bandwidth resource usage ratio.A model of sharing bandwidth allocation in multi-link is proposed,the features of link bandwidth allocation and QoS level are also discussed.The DBAMQ(dynamic bandwidth allocation and multi-level QoS) link access control algorithm is presented.In this algorithm,the bandwidth is readjusted according to variable QoS level.

针对传统的基于带宽请求链路接入控制算法(Link Bandwidth Require Control Algorithm,LBRCA)的接入成功率和系统带宽利用率不高的问题,设计了一种多链路接入共享带宽分配模型,分析了链路带宽分配和QoS等级的特点,提出一种动态带宽分配分级QoS链路接入控制算法DBAMQ(Dynamic Bandwidth Allocation and Multi-level QoS),该算法在保证某QoS等级的基础上允许动态地对系统的带宽进行重分配。

First, the traffic flow time series chaotic feature is extracted by chaos theory. pretreatment for traffic flow time series, and the wavelet neural networks model was build by this. Second, the chaotic mechanism and the chaotic probability is described. Based on chaotic learning algorithm, and the wavelet neural networks fast learning algorithm of traffic flow time series is designed based on chaotic algorithm. Last, a single-step and multi-step prediction of traffic flow chaotic time series is researched by BP neural networks, wavelet neural networks and wavelet neural networks based on chaotic algorithm. The results showed that the wavelet neural networks predictive performance is better than the BP networks and the wavelet neural networks by the simulation results and root-mean-square value.

首先,通过混沌理论提取了交通流量时间序列的混沌特征,并在此基础上建立了小波神经网络交通流量时间序列模型;接着,阐述了混沌学习算法的混沌机理、混沌产生的概率,设计了基于混沌算法的小波神经网络交通流量混沌时间序列快速学习算法;最后利用交通流量混沌时间序列对BP网络、非混沌算法的小波神经网络以及基于混沌算法的小波神经网络进行了单步预测和多步预测,并对预测结果的仿真图和真实值与预测值的方均根进行了比较,结果表明基于混沌学习算法的小波神经网络的预测性能明显优于应用BP网络和非混沌算法的小波神经网络。

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