多粒度全光网中的多层联合路由

多粒度交换技术利用波带级路由以及光纤级路由,可有效降低光交叉连接器的复杂度.但多粒度交换增加了光网络的逻辑层次结构,使得网络中的路由与资源分配问题更为复杂,因此,在多粒度全光网中实现多层联合路由是提高网络性能的关键.本文对多粒度交叉连接结构进行了分析,并对多粒度全光网中的多层联合路由问题进行了研究.     

稀疏阵列天线综合的遗传算法优化

通过遗传算法优化选择常规满阵中一定比例的工作单元,使阵列在欠饱和状态下达到窄波束低副瓣的要求。以单元的工作状态和激励幅度为优化参量,波束宽度和副瓣电平为适值函数,通过适值缩放和多种群进化竞争使遗传进化稳定地收敛到全局最优。详细分析了稀疏阵的单元布局、稀疏率及单元激励对优化阵列特性的影响。     

一种增强型冲突分解算法

冲突分解算法是一种能有效改善无线信道多址接入协议的方式。本文对传统的冲突分解算法——树形冲突分解算法和先到先服务冲突分解算法进行了深入研究和仿真，探讨了这两种算法的优点和不足之处，提出了一种增强型的冲突分解算法（Enhanced Splitting Algorithm，ESA）。该算法继承了树形冲突分解算法和先到先服务算法的优点，不仅考虑了碰撞分组产生的时间，还考虑了分组的产生间隔，从而有效地提高了冲突分解算法的性能。仿真结果显示ESA算法是一种可行的算法。     

数据挖掘技术在有线电视领域的应用

数据挖掘是近年来在数据库技术、统计学、人工智能、神经网络等学科的基础上发展起来的一门交叉学科，数据挖掘技术已经成功地应用于商业领域，随之又迅速地扩展到社会保险、医学、电信等领域，探讨和分析数据挖掘技术在有线电视领域的应用，并给出了系统体系结构和挖掘算法。     

POWER OPTIMIZATION OF FINITE STATE MACHINE BASED ON GENETIC ALGORITHM

Using state assignment to minimize power dissipation and area for finite state machines is computationally hard.Most of published results show that the reduction of switching activity often trades with area penalty.In this paper,a new approach is proposed.Experimental results show a significant reduction of switching activity without area penalty compared with previous publications.     

采用多级技术的DBF雷达CCAB算法

数字波束形成算法中,CCAB算法在较高信干噪比条件下具有一定优势。但是计算时需要求逆矩阵,在阵元数较多的情形下运算量极大,很难实时实现,严重制约了其进一步的应用。提出了一种基于原有CCAB算法的多级计算方法,可以有效地减少运算量。实验表明,该方法虽然其信噪比性能比普通CCAB算法有所下降,但是仍能在干扰方向上形成较深的零陷并有效地抑制干扰,能够进一步应用于实际工程中。     

Fitting the control parameters of a genetic algorithm: An application to technical trading systems design

This paper studies the problem of how changes in the design of the genetic algorithm (GA) have an effect on the results obtained in real-life applications. In this study, focused on the application of a GA to the tuning of technical trading rules in the context of financial markets, our tentative thesis is that the GA is robust with respect to design changes. The optimization of technical trading systems is a suitable area for the application of the GA metaheuristic, as the complexity of the problem grows exponentially as new technical rules are added to the system and as the answer time is crucial when applying the system to real-time data. Up to now, most of GAs applications to this subject obviated the question of possible “design dependence” in their results. The data we report, based on our experiments, do not allow us to refute the hypothesis of robustness of the GA to design implementation, when applying to technical trading systems tuning.     

基于约束优化的联想记忆模型学习算法

本文提出了一种对称互连神经元网络的学习策略,利用全局约束优化方法确定连接权。优化过程采用了梯度下降技术。这种学习算法可以保证训练样本成为系统的稳定吸引子,并且具有优化意义上的最大吸引域。本文讨论了网络的存储容量,训练样本的渐近稳定性和吸引域大小。计算机实验结果说明了学习算法的优越性。     

TEMIC射频卡的速率自适应读卡算法

提出种基于TEMIC射频卡Manchester编码的速率自适应读卡算法,并对该算法进行了说明和示例。     

A parallel version of the preconditioned conjugate gradient method for boundary element equations

The parallel version of precondition techniques is developed for matrices arising from the Galerkin boundary element method for two-dimensional domains with Dirichlet boundary conditions. Results were obtained for implementations on a transputer network as well as on an nCUBE-2 parallel computer showing that iterative solution methods are very well suited for a MIMD computer. A comparison of numerical results for iterative and direct solution methods is presented and underlines the superiority of iterative methods for large systems.