双层细晶粒Glass／Al／BiGaDyIG薄膜的磁光性能

快速循环晶化Ａｌ／ＢｉＧａＤｙＩＧ双层膜的研究结果表明，由于晶粒细化及膜层间干涉增强效应，在０．１～１．３μｍ膜厚范围．其平均有效法拉第角比单层膜增加了０．２５°，且随循环次数增加而增大。同时．部分ＡＩ３＋离子在退火期间扩散进石榴石的八面体和四面体位，导致居里温度下降（１４０～１６１μ）。这些结果对提高石榴石磁光盘信噪比以及增大记录密度是极有意义的。     

DC／DC变换器的磁罐粘接技术研究

在ＤＣ／ＤＣ变换器的组装工艺中,磁罐的粘接是一个关键问题。本文主要从粘接胶（膜）的选择以及工艺试验两方面进行了阐述,通过工艺试验确定了Ａｂｌｅｆｉｌｍ５０６膜为磁罐的最佳粘膜,并给出了此胶的工艺流程及操作要领。最后对此粘接工艺按ＧＪＢ２４３８附录Ｅ的要求进行了工艺鉴定。     

AlGaAs／InGaAs／GaAs异质结构中扩散噪声和扩散系数的蒙特卡罗研究

本文用蒙特卡罗法研究了ＡｌＧａＡｓ／ＩｎＧａＡｓ／ＧａＡｓ异质结构中二维电子气的扩散噪声和扩散系数．同ＡｌＧａＡｓ／ＧａＡｓ异质结构的情况一样，平行速度相关函数呈现振荡，但不同的是振幅随电子密度变化很小．另外，振幅在ＩｎＧａＡｓ层厚度增加时下降．用单个电子的相关函数和一组电子的位移方差两种不同方法计算了扩散系数．     

VLSI版图综合中的P／G网实体优化布线

本文提出了一种在通道内将Ｐ／Ｇ网与信号网的实体布线一体化考虑的优化布线策略，目的是在保证１００％布通的前提下，完成Ｐ／Ｇ网的平面化实体嵌入和信号网的实体布线，并使Ｐ／Ｇ走线对信号网走线的影响尽可能小。算法以提高布线区利用率、减小通道高度和减少通孔数为目标，实现总体性能的优化。系统实现的结果表明，本文算法所采用的策略是可行的、有效的。     

TG28磁光玻璃

介绍了高Ｖｅｒｄｅｔ常数法拉第旋光玻璃的研究结果。选择了Ｔｂ２Ｏ３一Ｂ２Ｏ３—Ａｌ２Ｏ３—ＳｉＯ２系统为基础，研究玻璃形成．得到了高Ｔｂ２Ｏ３含量下稳定的玻璃组成ＴＧ２８．并获得了０．５Ｌ规模下高质量的玻璃样品．研究了ＴＧ２８玻璃的物理化学性质及熔制工艺．实验表明ＴＧ２８玻璃的Ｖｅｒｄｅｔ常数可高达—９７．４４Ｒａｄ／Ｔ．ｍ。此结果表明了进一步提高Ｖｅｒｄｅｔ常数的可能性．     

新型掺Bi的YIG磁光薄膜

对用于磁光法拉第旋转器件的掺Ｂｉ的ＹＩＧ薄膜进行了介绍与分析，这种新型磁光薄膜（ＹｂＴｂＢｉ）３（ＦｅＧａ）５Ｏ１２是采用液相外延技术在ＣａＭｇＺｒ：ＧＧＧ晶片的（１１１）方向生长的，通过合理的配方及工艺生长出了成份均匀，光吸收小，在波长λ＝１．３１μｍ和λ＝１．５５μｍ时，插损分别为０．３ｄＢ和０．２ｄＢ，法拉第旋转角分别为２４００°／ｃｍ和１６００°／ｃｍ的薄膜，经抛光至２９０μｍ的厚度，法拉     

磁隧穿振荡研究GaAs／AlAs双势垒结构中的Γ—X电子态混合

报道了非对称ＧａＡｓ／ＡｌＡｓ双势垒结构（ＤＢＳ）中的Γ－Ｘ－Γ磁隧穿振荡现象，用磁场倒数周期求得ＡｌＡｓ层中Ｘ谷和ＧａＡｓ层中Γ谷之间的能带不连续值与通常公认值符合很好，良好的振荡特性可作为定量研究Γ－Ｘ耦合强度的灵敏的实验办法。     

1．55μm InGaAsP／InPDH激光器中的0．95μm发光带与Auger复合

报道了在１．５５μｍＩｎＧａＡｓＰ／ＩｎＰ激光器中发现的０．９５μｍ波长高能发光峰的一系列实验结果，并通过分析肯定了ＩｎＧａＡｓＰ有源区的Ａｕｓｅｒ复合是造成载流子向两侧ＩｎＰ限制层漏泄的主要原因，也是影响１．５５μｍＩｎＧａＡｓＰ／ＩｎＰＤＨ激光器Ｔ０值的主要因素。     

γ／X^α约束下的动态光散射函数

本文给出了激光散射处在γ／Ｘ＾α约束模型下散射粒子的速度相关函数及位移二阶矩函数,并将所得结果应用到动态光散射技术的理论研究中：将入射光和散射光均视为理想平面光波,将散射作视为γ／Ｘ＾αＸＱＧＫＧＨ Ｒ ＡＥＴ ＴＭＤＦＯＵＧ ＢＢ ＷＹＳＷＧＫ ,ＦＧＨＩＦ     

静磁表面波传输各向异性研究

建立了在实际ＹＩＧ／Ａｌ２Ｏ３／金属层状结构中的静磁表面波各向异性色散理论，利用数值计算方法研究了偏离正常传输方向φ角时的波矢－频率（ｋ－ｆ）和群延时－频率（τｒ－ｆ）的色散特性，随φ角的增大，色散加剧，群延时增大，但可激励静磁表面波的理论带宽变窄，φ存在一极限值，且在靠近静磁表面低频限的频率范围内φ的极限值也是色散的，与Ａｌ２Ｏ３层的厚度有关。     

k-out-of-m system availability with minimum-costallocation spares

An optimization method for determining the number of spare units that should be allocated to a k-out-of-m system to minimize the system-spares cost yet attain the specified system availability is presented. The objective function for optimization is a nonlinear integer type. The optimization method is a variation of the simplex search technique used for continuous functions. The optimization problem is cast in a form that minimizes the system-spares cost, with the required system availability as an inequality constraint. Results obtained by using the proposed optimization technique, as well as the computation time required for optimization, are compared to those for methods developed specifically for dealing with nonlinear integer problems. The method is simple, easy to implement, and yet very effective in dealing with the spare allocation problem for k-out-of-m:F systems     

An effective multiuser receiver for DS/CDMA systems

Multiuser detection (MUD) is a key technique for combating multiple access interference (MAI) in CDMA systems. We propose a simple and effective multiuser receiver, which we refer to as the objective function based multiuser detector (OFMUD). This is a successive multistage joint detector based on the statistical optimization of an objective function. Two objective functions are considered in this paper. The first one is based on a maximum likelihood solution, and the second one is based on the least squared error solution. A key feature of the proposed detector is that among all the K user bits, we update the estimate of one and only one bit (the one that is most likely to be wrong) in every stage. Analytical and numerical results show that significant performance improvement can be achieved compared with the conventional DS/CDMA receiver. At the same time, the near-far problem is alleviated. In addition, it is shown that the proposed receiver can outperform the popular multiuser parallel interference cancellation receiver in most cases with a smaller computational cost     

Electrical defibrillation optimization: an automated, iterativeparallel finite-element approach

To date, optimization of electrode systems for electrical defibrillation has been limited to hand-selected electrode configurations. Here, the authors present an automated approach which combines detailed, three-dimensional (3-D) finite-element torso models with optimization techniques to provide a flexible analysis and design tool for electrical defibrillation optimization. Specifically, a parallel direct search (PDS) optimization technique is used with a representative objective function to find an electrode configuration which corresponds to the satisfaction of a postulated defibrillation criterion with a minimum amount of power and a low possibility of myocardium damage. For adequate representation of the thoracic inhomogeneities, 3-D finite-element torso models are used in the objective function computations. The CPU-intensive finite-element calculations required for the objective function evaluation have been implemented on a message-passing parallel computer in order to complete the optimization calculations in a timely manner. To illustrate the optimization procedure, it has been applied to a representative electrode configuration for transmyocardial defibrillation, namely the subcutaneous patch-right ventricular catheter (SP-RVC) system. Sensitivity of the optimal solutions to various tissue conductivities has been studied. Results for the optimization of defibrillation systems are presented which demonstrate the feasibility of the approach     

基于有限长FEM/BEM提取COM参量

介绍了一种理论提取耦合模式模型(COM)参量的方法。利用有限长有限法/边界元法(FEM/BEM)计算声表面波同步单端对谐振器的导纳曲线,根据导纳曲线与表面波色散特性相关的特征量,通过解析计算、单变量拟合、再次单变量拟合及两变量拟合4个步骤依次提取出全部COM参量。与传统方法相比,该方法简单、稳定、可靠。根据得到的COM参量对一种混合结构的滤波器进行了模拟,与直接使用FEM/BEM得到的结果符合较好,验证了所提取的COM参量的准确性。     

用多目标进化算法搜索MOPs的鲁棒Pareto最优解

 搜索鲁棒Pareto最优解是多目标进化算法(MOEA)研究的一个重要方面.目前,优化"原目标函数"的传统MOEA与基于"有效目标函数"的MOEA (Eff-MOEA)在搜索鲁棒Pareto最优解时都易丢失某些性质的解.为解决这一缺陷,本文定义了一种新的鲁棒Pareto最优解,提出了一种新的搜索鲁棒Pareto最优解的MOEA(MOEA/R),MOEA/R将多目标鲁棒优化问题(MROP)转化成两目标问题来优化,一个目标为解的质量,另一个目标为解的鲁棒性,每一目标均对应一子优化问题.通过与NSGA-Ⅱ及Eff-MOEA的对比分析,结果表明MOEA/R的结果较好,更重要的是本文探索了一种新的搜索鲁棒Pareto最优解的思想.     

Unconstrained Face Detection of Multiple Humans Present in the Video

Accurate and fast localization of randomly deployed sensor nodes is needed for many applications in wireless sensor networks. Localization also benefits in recognizing the geographically area where an event took place. There is no meaning of any event information without the knowledge of its location coordinates. DV-Hop is one of the main range free localization technique, which estimates the position of nodes using distance vector. Particle swarm optimization is suitable for the localization issues because of its fast computing speed and high precision. To further reduce the positioning error, the traditional DV-Hop localization algorithm based on single objective optimization algorithm is converted into a multi objective optimization algorithm. In our proposed scheme, we have considered six different single objective functions and three different multi objective functions. In this paper, a multi objective particle swarm optimization based DV-Hop localization is proposed in 3-dimensional wireless sensor networks. The proposed functions has been evaluated on the basis of computation time, average localization error and localization error variance. The simulation results show that our proposed multi objective function performs better as compared to traditional single objective function.

     

轻小型折射/衍射混合自由曲面塑料微光夜视仪物镜设计

微光夜视仪是飞行员夜间行驶的重要观瞄、导航设备,物镜是微光夜视仪的重要组成部分。文中在一个6 片式初始镜头的基础上, 设计了一个传统的全球面式物镜, 并提出了一种改进型的折射/衍射混合自由曲面塑料物镜结构,给出了详细的设计步骤并对两个系统进行了像质评价,对比分析了两个结构的性能,结果表明,改进型系统不仅在垂轴色差、畸变、像散、调制传递函数等光学性能上优于传统的全球面式物镜,而且在重量、总长以及最大口径方面也有大大改善,设计满足微光夜视仪物镜成像要求,并实现了物镜的轻小型和低成本,为现代新型微光夜视仪物镜的轻小型设计提供了一种新的途径。     

Image reconstruction using interval simulated annealing in electrical impedance tomography

Electrical impedance tomography (EIT) is an imaging technique that attempts to reconstruct the impedance distribution inside an object from the impedance between electrodes placed on the object surface. The EIT reconstruction problem can be approached as a nonlinear nonconvex optimization problem in which one tries to maximize the matching between a simulated impedance problem and the observed data. This nonlinear optimization problem is often ill-posed, and not very suited to methods that evaluate derivatives of the objective function. It may be approached by simulated annealing (SA), but at a large computational cost due to the expensive evaluation process of the objective function, which involves a full simulation of the impedance problem at each iteration. A variation of SA is proposed in which the objective function is evaluated only partially, while ensuring boundaries on the behavior of the modified algorithm.     

Joint Optimization of Capacity and Flow Assignment in a Packet-Switched Communications Network

This paper presents a global optimal solution technique for the joint optimization of link capacity and flow assignment (CFA) in a packet-switched communications network,m-M/M/1queueing systems to model existing networks are considered. A continuous lower bound of the average packet delay is used in the formulation of the cost objective function for the capacity and flow assignment. The cost objective function thus formulated is shown to be convex with respect to the network multicommodity flow. This convexity ensures the global optimal solution to the CFA problem via the flow deviation (FD) method. Refinement of the CFA optimization techhique to allow optimal discretization of the continuous solutions to discrete solutions is presented based on dynamic programming and iterations of Flow Optimization and Capacity Optimization. Application examples of these optimization procedures are illustrated.     

Resource allocation in OFDMA networks based on interior point methods

This paper studies a joint optimization problem of sub‐carrier assignment and power allocation in orthogonal frequency division multiple access (OFDMA) wireless networks. A major challenge in solving the optimization problem is non‐convexity caused by the combinatorial nature of sub‐carrier assignment problem and/or non‐convex objective functions. To address the combinatorial complexity, we formulate the resource allocation problem as an optimization problem with continuous variables. We propose a novel approach based on a penalty function method and an interior point method (PM/IPM) to solve the problem. In specific, using a two‐step implementation, the penalty method is applied first to convert the non‐convex feasible region to a convex one. Then, the interior point method is deployed to solve the problem which is non‐convex only in the objective function. To evaluate the performance of PM/IPM, we apply a genetic algorithm (GA) that achieves near optimal solutions of the problem by iterative searching. Copyright © 2009 John Wiley & Sons, Ltd.