球解码的改进算法

文中首先对MIMO系统启发式算法中的BLAST算法和球解码(CL算法)进行了研究.然后,在前面介绍的相关知识基础上,提出了一种新的球解码算法.该改进算结合BLAST算法计算量小和球解码算法(CL算法)误码性能好的优点而提出的.改进算法在牺牲一定误码性能的情况下,换取算法计算量的大幅度下降.仿真结果表明了这种改进算法的有效性.     

Group-Scheduling for Multi-Service Optical Burst Switching (OBS) Networks

We propose a new burst scheduling mechanism for Optical Burst-Switched (OBS) networks. The new approach is made possible by gathering data bursts into groups and performing the scheduling decision for each group collectively. In OBS group-scheduling, bursts will not be considered for scheduling until a pre-defined time period elapses, during which the group of burst header packets would be gathered. By transforming a set of data bursts into a set of corresponding time intervals, the problem of scheduling these bursts is transformed into a combinatorial optimization problem. Graph algorithms are applied to obtain the maximum number of non-overlapping bursts. The proposed OBS group-scheduling scheme is shown to improve the performance of OBS networks over existing scheduling schemes in terms of burst loss probability and channel utilization. With an extension through a sequential optimization, using a Branch-and-Bound technique, the proposed scheme can support multiple classes of service. It is shown that the new scheduling approach has several desired characteristics including fairness and service differentiability among classes in terms of burst loss probability and channel utilization.     

一类0-1背包问题的启发式网络策略模型与算法

针对遗传算法(GA)易陷入局部最优解、搜索精度低等缺点,提出了网络启发式策略的遗传算法(NSHGA),并将其成功地应用于0-1背包问题的求解。该算法采用网络节点关联策略,使算法具有良好的全局寻优能力。同时引入网络节点矩阵优化,利用其精细的局部遍历搜索性能,使算法具有较高地搜索精度。实例仿真结果表明,NSHGA算法可有效避免基本GA算法的早熟收敛,且具有寻优能力强、搜索精度高等特点。此外,与基本遗传算法仿真相比,可明显提高0-1背包问题求解的精度。     

Ant colony optimisation–direct cover: a hybrid ant colony direct cover technique for multi-level synthesis of multiple-valued logic functions

The use of non-binary (multiple-valued) logic in the synthesis of digital systems can lead to savings in chip area. Advances in very large scale integration (VLSI) technology have enabled the successful implementation of multiple-valued logic (MVL) circuits. A number of heuristic algorithms for the synthesis of (near) minimal sum-of products (two-level) realisation of MVL functions have been reported in the literature. The direct cover (DC) technique is one such algorithm. The ant colony optimisation (ACO) algorithm is a meta-heuristic that uses constructive greediness to explore a large solution space in finding (near) optimal solutions. The ACO algorithm mimics the ant's behaviour in the real world in using the shortest path to reach food sources. We have previously introduced an ACO-based heuristic for the synthesis of two-level MVL functions. In this article, we introduce the ACO–DC hybrid technique for the synthesis of multi-level MVL functions. The basic idea is to use an ant to decompose a given MVL function into a number of levels and then synthesise each sub-function using a DC-based technique. The results obtained using the proposed approach are compared to those obtained using existing techniques reported in the literature. A benchmark set consisting of 50,000 randomly generated 2-variable 4-valued functions is used in the comparison. The results obtained using the proposed ACO–DC technique are shown to produce efficient realisation in terms of the average number of gates (as a measure of chip area) needed for the synthesis of a given MVL function.     

基于反复加深的模糊启发式搜索算法及其学习性质研究

本文基于反复加深和动态修改启发式估价函数这一机制。提出了模糊启发式搜索算法ＦＩＤＡ和Ｉｍｐｒｏｖｅｄ－ＦＩＤＡ。针对模糊启发式估价函数通常难以设计这一问题，提出了可用于模糊启发式估价函数学习的学习算法ＬＦＩＤＡ。     

Efficient recursive least squares parameter estimation algorithm for accurate nanoCMOS variable gain amplifier performances

ABSTRACT

With the aggressive scaling of integrated circuit technology, parametric estimation is a critical task for designers who looked for solutions to the challenges of some Nanoscale CMOS parameters. This paper presented the prediction of primary parameters of CMOS transistor for 16 nm to 10 nm process nodes using both of Bisquare Weights (BW) method and a novel recursive least squares (RLS) parameter estimation algorithm. The proposed RLS algorithm consists of the minimisation of a quadratic criterion relating to the prediction error in order to attain the best estimated parameters of the developed mathematical model. The obtained results thanks to the proposed RLS algorithm were better than those reached using the BW method. Comparisons between Predictive Technology Model (PTM) data and parameters estimated with RLS algorithm were made to check the validity and the consistency of the proposed algorithm. These predicted primary parameters were helpful to estimate and to optimise the performances of the Variable Gain Amplifier (VGA) which was a basic circuit element with a key role in the design of new upcoming receivers.     

模块度优化启发式算法应用

模块度优化的启发式快速算法常常用来检测复杂网络中的社团结构.较之其余的社团检测方法,该算法在计算时间上更具优势,而且用模块度衡量发现检测社团的质量很高.运用模块度优化启发式算法划分空手道俱乐部网络、大学足球俱乐部网络和区域贸易网络等,并对其结构和功能做出一定的分析.特别地,针对贸易网络中自由贸易区往往表现为一个社团的特点,以221个国家或地区为研究对象,对贸易协定与地域之间的关系做了大量的实证研究.首先,从世贸组织网站上采集了区域贸易协定中国家之间贸易的数据;其次,通过模块度启发式算法进行社团划分,共得出7个主要的贸易区,其中欧盟自由贸易区的社团表现极为明显;最后,从社团结构的表现形式推断实际区域间的贸易情况.     

变流量节能系统动态监测及实时调节系统设计分析

为提高变流量节能系统自适应性能和实时调节能力,提出基于双启发式动态规划的变流量节能系统动态监测及实时调节系统设计方法,构建变流量节能动态监测及实时调节控制对象模型,以供水流量及一次侧的供水温度、供水流量为初始约束参量设计系统的控制规则。在此基础上,结合双启发式动态规划模式并采用模糊优化分配控制策略,对系统进行调节和控制,通过线性规划学习方法,实现变流量节能动态监测及实时调节。仿真结果表明,采用该方法进行变流量节能系统动态监测及实时调节的自适应性能较好,各时段流量预测误差曲线波动介于-1.5至1.5之间,且热负荷值与预测热负荷之间相对误差最大值为2.5%,误差较低。     

基于不确定性任务的多星调度启发式算法

根据多星测控中用户提出的不确定性任务的特点,建立多星调度基于不确定性任务的数学模型。提出任务支持时间最大化作为启发式准则,以及弧段分割法调整测控资源冲突。在此基础上,结合资源均衡原则和卫星优先级策略,提出了基于不确定性任务的多星调度启发式算法。最后,算法运用在10星6站的调度问题中,仿真结果表明算法是可行的。     

基于启发式调度的OpenFlow网络规则一致更新方案

针对OpenFlow网络在状态转换过程中会暂时性出现转发回路、路由黑洞和违反访问控制策略等问题,提出了一种基于启发式调度的规则一致更新方案.首先,设计基于谓词的更新分解算法,利用并行网络属性验证技术得到子更新依赖图;其次,采用任务图生成算法对子更新依赖图进行分割,降低更新调度的复杂度;之后,设计启发式更新调度算法,采用规则增删操作交替执行策略,减少交换机的规则存储开销,并通过建立更新实施和监听并发执行机制,提升更新效率.仿真实验从更新时间开销和更新过程中交换机规则存储开销两方面验证了方案的有效性.