Statistical DOE-ILP based power-performance-process (P3) optimization of nano-CMOS SRAM

As technology continues to scale, maintaining important figures of merit of Static Random Access Memories (SRAMs), such as power dissipation and an acceptable Static Noise Margin (SNM), becomes increasingly challenging. In this paper, we address SRAM instability and power (leakage) dissipation in scaled-down technologies by presenting a novel design flow for simultaneous power minimization, performance maximization and process variation tolerance (P3) optimization of nano-CMOS circuits. The 45 and 32 nm technology node standard 6-Transistor (6T) and 8T SRAM cells are used as example circuits for demonstration of the effectiveness of the flow. Thereafter, the SRAM cell is subjected to a dual threshold voltage (dual-V_Th) assignment based on a novel statistical Design of Experiments-Integer Linear Programming (DOE-ILP) approach. Experimental results show 61% leakage power reduction and 13% increase in the read SNM. In addition, process variation analysis of the optimized cell is conducted considering the variability effect in twelve device parameters. To the best of the authors' knowledge, this is the first study which makes use of statistical DOE-ILP for optimization of conflicting targets of stability and power in the presence of process variations in SRAMs.     

抗DPA攻击的功耗平衡SRAM设计

A power balance static random-access memory(SRAM) for resistance to differential power analysis(DPA) is proposed. In the proposed design, the switch power consumption and short-circuit power consumption are balanced by discharging and pre-charging the key nodes of the output circuit and adding an additional shortcircuit current path. Thus, the power consumption is constant in every read cycle. As a result, the DPA-resistant ability of the SRAM is improved. In 65 nm CMOS technology, the power balance SRAM is fully custom designed with a layout area of 5863.6 μm~2.The post-simulation results show that the normalized energy deviation(NED) and normalized standard deviation(NSD) are 0.099% and 0.04%, respectively. Compared to existing power balance circuits, the power balance ability of the proposed SRAM has improved 53%.     

基于Spark的改进随机森林算法

针对基于单机的经典随机森林算法无法满足海量数据处理需求的问题,文中采用Spark分布式存储计算技术设计并实现了改进的随机森林算法。首先计算特征的重要程度,将特征分为公共特征、独有特征和非重要特征;然后按顺序和比例分别在各个特征子空间中随机选择特征;最后通过Spark集群进行实验,分析改进的随机森林算法分类性能、加速比和效率。结果证实改进的算法提高了随机森林构建效率,可以用来解决海量数据挖掘问题,具有良好的可扩展性。     

Analysis and design of optimum interleaver for iterative receivers in IDMA scheme

In this paper, we propose a new tree based interleaver (TBI) to generate different chip‐level interleaving sequences for different users in an interleave division multiple access (IDMA) system, which reduces computational complexity. This method of generation also solves the memory cost problem and reduces the amount of information exchange between mobile stations (MSs) and base stations (BSs) required to specify the interleaver. Simulation results are presented to show that the proposed interleavers perform well as compared to random interleavers in an IDMA system. Copyright © 2008 John Wiley & Sons, Ltd.     

单片式彩色LCOS微显芯片电路设计

介绍一种单片式彩色LCOS微显芯片的电路设计。这种LCOS芯片配置合适的光机及电路系统可用于单片式LCOS彩色背投电视或其它投影产品。与传统场序彩色LCOS微显芯片类似，该芯片的主要模块由行扫描驱动器、数据驱动器和象素驱动矩阵三大部分组成。不同的是二者的行寻址方式不同，传统场序彩色LCOS采用的是逐行扫描法，而此处介绍的彩色LCOS采用的是随机寻址方式，将红、绿、蓝三种数据几乎同时写入象素矩阵，配合滚动的光照显示彩色图像。单片式LCOS系统与三片式LCOS系统相比可以节省微显芯片及配套电路系统数目，从而大大节约成本，在背投电视和其他投影产品产业中有很大的实用价值。     

随机大气信道对激光信号传输影响的分析

首先介绍了激光信号通过随机大气信道时,大气中的气体分子和大气气溶胶离子、尘埃、雾、雨、霾等对激光信号的吸收和散射效应,造成了对激光信号的能量衰减,接着分析了大气湍流效应对光信号传输的影响,即光束的闪烁、弯曲、分裂.最后,对于不同大气条件下激光信号的传输进行了实验研究,给出了在同一时刻的不同天气条件、在同一天的不同时刻及不同能见度条件下的测试结果,并就实验现象进行了分析.所得到的结果很好地反映了理论分析,为大气通信提供了一定的指导.     

基于可控随机变换的分形树生成算法及实现

分形树的生成算法是自然景物模拟中的热点问题,针对目前生成算法中的运行显示速度慢,树形变化少,颜色单一等问题,提出了一种可控随机交换的分形树生成算法.该算法对分形树的生成参数进行随机控制.给出了该算法的核心思想及实现过程,仿真实验得到了较好的生成显示速度及多姿态、多色彩的具有三维真实感的分形树.算法具有一定的通用性并可为其他自然景物的模拟提供较高的研究参考价值.     

某液晶显示器温控电路板可靠性强化试验技术研究

研究了某液晶显示器浊控电路板可靠性强化试验技术，对相关的试验过程和试验结果进行了详细的描述与分析，说明了可靠性强化试验技术在激发产品潜在缺陷、提高产品固有可靠性方面的可行性和有效性。     

图像多样性重排序技术综述

近年来互联网呈现出了爆炸式的增长,而与日常生活息息相关的图像资源变得更加重要,如何能够准确地获取所需的图像资源是当前多媒体搜索领域需要重点解决的问题。目前的大多工作围绕图像的相关性搜索重排序展开,对多样性搜索重排序的研究较少。相关性重排序是指对于返回结果来说,都是将相关的样本排在结果集的前列,但是很少考虑样本相互之间的联系,而多样性重排序是为了提高返回结果的多样性,也就是覆盖主题的多样性,以降低相关重排序中带来的信息冗余问题。文中对当前常见的几种算法评价并进行比较,并通过不同于文本重排的评价准则对性能进行评价。