基于混合优化策略的微分进化改进算法

微分进化算法具有控制参数少、鲁棒性强、易于使用等优点，并具有不同的优化策略．本文在对微分进化算法各优化策略性能进行分析的基础上，提出了基于混合优化策略的微分进化改进算法．改进算法的主要思想是将种群中的个体随机地分成两组，每组采用不同的优化策略．利用五个标准的优化算法测试函数对改进算法的收敛速度和搜索成功率进行了测试，并与动态微分进化算法和微粒群算法进行了比较．实验结果表明，本文提出的改进算法在保证算法搜索成功率的同时，大大提高了算法搜索效率．     

基于动态交换策略的快速多目标粒子群优化算法研究

本文提出了一种基于动态交换策略的快速多目标粒子群优化算法,通过把初始种群分割成Pareto和Non_Pareto集合,并在迭代过程中对Pareto解集进行动态调整,从而较好地完成了多目标优化算法对Pareto解集的搜索和逼近.实验和应用实例均表明了该算法的有效性和快速性,并通过性能指标ER的计算验证了本算法优于某些同类的多目标优化算法.     

求解连续空间优化问题的量子粒子群算法

为提高粒子群算法的搜索能力和优化效率并避免早熟收敛,将量子进化算法融合到粒子群算法中,提出一种求解连续空间优化问题的量子粒子群优化算法.用量子位的概率幅对粒子位置编码,用量子旋转门实现粒子移动,完成粒子搜索;用量子非门实现变异,提高种群多样性.因每个量子位有两个概率幅,故每个粒子同时占据空间两个位置,在粒子数目相同时,能加速粒子的搜索进程.实验结果表明,本算法优于基本粒子群算法.     

GNSS接收机基带处理电路低功耗设计综述

通过时GNSS接收机基带处理电路低功耗设计技术进行调研和总结,发现大部分技术可归属于两个层次：电路级优化技术和算法级优化技术。电路级优化技术主要包括低功耗的并行相关器的设计、多通道的时分复用、多普勒补偿后的信号下采样、低功耗累加器的使用等技术;算法级优化技术是指接收机的间歇工作方式（在不需要定位输出时,使接收机运行在低功耗模式）,主要通过接收机的高级电源管理系统、快速首次定位、重新捕获定位等技术实现。本文对这些方法进行了总结和对比,给出了两个层次优化技术的优缺点。     

天空双基地预警雷达空间同步效果优化

天空双基地预警雷达空间同步效果评估与优化是其空间同步技术的重要一环。首先,提出了空间同步效果的评估指标,分析其三大影响因素;其次,针对每个波位需要的波束驻留时间不同的问题,提出了脉冲积累优化方案,对其工作流程和相关参数计算进行推导;然后,从对波位编排灵活控制的角度提出了波位编排优化方案;最后,设计仿真实验对两种同步效果优化方案进行验证。仿真结果表明：两种优化方案可以使得接收信噪比和空间覆盖率的空间分布更加均匀,提高了发射能量的利用效率,有助于空间同步效果的优化。     

基于对比度最优准则的自聚焦优化算法研究

对比度最优自聚焦算法是一种基于图像幅度的自聚焦方法.本文将对比度最优自聚焦算法等效为一个求解局部最优解的优化模型.结合实际SAR(Synthetic Aperture Radar)系统的特征采用了两种解决此优化问题的算法:黄金分割和Fibonacci级数法,和传统方法相比,这两种优化方法明显提高了对比度最优自聚焦算法的运算效率.     

率失真优化技术及其在图像编码中的研究

率失真优化技术能够不受编码结构和技术的限制有效地提高图像／视频压缩编码系统的性能,尤其在标准已定义的场合,因而一直以来都是热点的研究内容。围绕率失真理论,介绍了率失真优化的原理和两种常用的率失真优化方法,比较了它们的优缺点,最后研究了如何将失真优化技术和压缩编码系统中的关键技术相结合以提高系统性能。     

Optimal signaling and detector design for power-constrained binary communications systems over non-gaussian channels

In this letter, joint optimization of signal structures and detectors is studied for binary communications systems under average power constraints in the presence of additive non-Gaussian noise. First, it is observed that the optimal signal for each symbol can be characterized by a discrete random variable with at most two mass points. Then, optimization over all possible two mass point signals and corresponding maximum a posteriori probability (MAP) decision rules are considered. It is shown that the optimization problem can be simplified into an optimization over a number of signal parameters instead of functions, which can be solved via global optimization techniques, such as particle swarm optimization. Finally, the improvements that can be obtained via the joint design of the signaling and the detector are illustrated via an example.     

基于故障管理和性能管理的网络优化方法

介绍了网络管理在网络优化中的作用,通过指导网络管理员在充分利用目前网络资源的前提下进行网络优化,从而达到降低网络优化成本的目的.网络管理技术中的故障管理及性能管理极大提高了网络的可见性.最后对网络优化的发展趋势及网管系统在其中所能起到的作用进行了展望.     

中继辅助OFDM系统功率优化

主要讨论了DF型中继辅助OFDM通信系统中的功率优化方案,并针对最优的功率优化方案很难得到闭合解的问题,提出了一种迭代的功率优化算法。这种迭代算法将DF型中继辅助OFDM通信系统中,单个子载波上源节点与中继节点间的功率分配问题以及各个子载波之间的功率优化问题分开,首先计算给定某个子载波上发送总功率下源节点与中继节点间的功率分配,然后在此基础上进一步优化子载波间的功率分配,并迭代逼近最优解。实验证明,在给定传输总功率的情况下,与传统的等功率分配相比这种迭代的优化方案可以获得较高的系统性能优势。     

Planar antenna pattern nulling using differential evolution algorithm

Differential evolution algorithm is used for the pattern synthesis of planar antenna arrays with prescribed pattern nulls by position-only and position-amplitude optimization. The position-only optimization for a planar array allows null synthesis in any prescribed direction. For planar antenna array thinning it is necessary to use position-amplitude optimization for problems involving more than two nulls.     

Energy‐Aware Hybrid Cooperative Relaying with Asymmetric Traffic

In this paper, we study an asymmetric two‐way relaying network where two source nodes intend to exchange information with the help of multiple relay nodes. A hybrid time‐division broadcast relaying scheme with joint relay selection (RS) and power allocation (PA) is proposed to realize energy‐efficient transmission. Our scheme is based on the asymmetric level of the two source nodes’ target signal‐to‐noise ratio indexes to minimize the total power consumed by the relay nodes. An optimization model with joint RS and PA is studied here to guarantee hybrid relaying transmissions. Next, with the aid of our proposed intelligent optimization algorithm, which combines a genetic algorithm and a simulated annealing algorithm, the formulated optimization model can be effectively solved. Theoretical analyses and numerical results verify that our proposed hybrid relaying scheme can substantially reduce the total power consumption of relays under a traffic asymmetric scenario; meanwhile, the proposed intelligent optimization algorithm can eventually converge to a better solution.     

应用边界扫描技术提高电路板可测试性的两种优化问题

边界扫描测试技术很好地解决了VLSI电路诊断、测试的困难问题，得到了广泛的应用。作者在查阅大量文献资料的基础上．总结出了边界扫描技术在提高电路板可测试性上的两种优化问题：即设计过程中设计复杂性和测试性改善的优化，以及在测试生成算法中紧凑性与完备性优化的问题，论文详细分析了这两种问题，分析比较了相关的优化算法，并对这两种优化问题未来的发展方向进行了预测。     

Two-pole approximation for interconnect design and optimization

Firstly, an approach to find two approximate poles for capturing the system behaviour of interconnect network is presented. Secondly, two parameters, the damping ratio and natural undamped frequency, are expressed as functions of the two poles. These two parameters are used to define an objective function and constraints, which form a constrained multivariable nonlinear optimization problem. The optimization problem is solved using a gradient projection method. One major advantage of our approach is the ability to explicitly control the maximum overshoots at the observation points.     

Blind signals separation with genetic algorithm and particle swarm optimization based on mutual information

Blind source separation technique separates mixed signals blindly without any information on the mixing system. In this paper, we have used two evolutionary algorithms, genetic algorithm and particle swarm optimization for blind source separation. In these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. In order to evaluate and compare the performance of these methods, we have focused on separation of noisy and noiseless sources. Simulations results demonstrate that the proposed method for employing fitness function has rapid convergence, simplicity and a more favorable signal to noise ratio for separation tasks based on particle swarm optimization and continuous genetic algorithm than binary genetic algorithm. Also, particle swarm optimization enjoys shorter computation time than the other two algorithms for solving these optimization problems for multiple sources.     

基于凸优化的共形阵二维波束优化算法研究

传统波束优化手段应用于共形阵二维波束优化时,存在旁瓣水平高的问题.文中基于凸优化理论,提出了两种适用于共形阵列二维波束旁瓣优化的二阶锥规划方法.第一种是设定主瓣宽度下的最低旁瓣波束形成,第二种是设定期望旁瓣级的高增益等旁瓣波束形成.仿真结果表明相比于常规波束形成和其它波束优化方法,第一种方法在相同主瓣宽度约束条件下可以...     

基于GIS和差分进化粒子群的变电站选址方法

文中提出了一种基于地理信息系统(GIS)和差分进化改进粒子群的配电网变电站优化选址方法。该方法利用GIS确定变电站数量,基于变电站投资运行费用建立有约束条件的目标函数,采用粒子群算法进行变电站选址优化。针对粒子群算法易陷入局部最优且收敛速度慢的问题,借助差分进化引入两个变异因子,在提升粒子群算法收敛速度的同时,避免其陷入局部最优。算例分析结果表明,该方法具有较好的寻优能力和收敛特性,能够有效实现变电站选址优化。     

Is Search Really Necessary to Generate High-Performance BLAS?

A key step in program optimization is the estimation of optimal values for parameters such as tile sizes and loop unrolling factors. Traditional compilers use simple analytical models to compute these values. In contrast, library generators like ATLAS use global search over the space of parameter values by generating programs with many different combinations of parameter values, and running them on the actual hardware to determine which values give the best performance. It is widely believed that traditional model-driven optimization cannot compete with search-based empirical optimization because tractable analytical models cannot capture all the complexities of modern high-performance architectures, but few quantitative comparisons have been done to date. To make such a comparison, we replaced the global search engine in ATLAS with a model-driven optimization engine and measured the relative performance of the code produced by the two systems on a variety of architectures. Since both systems use the same code generator, any differences in the performance of the code produced by the two systems can come only from differences in optimization parameter values. Our experiments show that model-driven optimization can be surprisingly effective and can generate code with performance comparable to that of code generated by ATLAS using global search.     

使用粒子群算法进行特征选择及对支持向量机参数的优化

特征选取和参数设置是提升支持向量机分类器的效果的两个主要手段.为了将两者结合起来,实现同步优化,以达到更好的分类效果,设计了一种基于粒子群算法的分类器优化算法.新算法对粒子采用2进制编码的,设计适合的目标函数,同步进行特征选择和支持向量机参数的优化.经过对比验证,新方法能够更加准确的得到待分类数据的特征子集跟支持向量机参数,最终得到更优的处理结果.     

Optimized design of a complete three-phase PWM-VS inverter

This paper introduces and discusses the optimized design of power electronic circuits as a tool for flexible and fast computer-aided design. A design center concept, based on both optimization and design, is defined. The concept is used on a complete three-phase voltage-source inverter (VSI), with a focus on the optimization part. The optimization is performed in order to obtain maximum efficiency by changing the gate-drive conditions, like gate resistances and gate-drive supply. Another optimization is performed, where the thermal characteristic of the diode and insulated gate bipolar transistor (IGBT) is taken into account. A loss model of a complete three-phase VSI is developed. Based on known data for the IGBTs, the diodes and inverter circuit, the outputs of the proposed optimizer are two gate-drive resistances, a gate-drive supply and a load current, which give the inverter the highest efficiency. It is concluded the optimization points of the inverter design are different using the two proposed optimization criteria. The highest load current for the same devices is found for the inverter when the thermal effects are included. Finally, parts of the loss model are verified with experiments