基于多曝光的高动态图像合成的噪声处理

针对在高动态范围图像合成的过程中有噪声影响图像的质量这一问题,采取一种基于多曝光图像的高动态范围图像合成降噪算法。通过对各曝光图像的灰度数据进行提取、整理、分析,能合成代表原始场景光线分布的亮度图像。通过分析噪声对高动态范围图像合成质量的影响,提出在图像合成前将图像中含有的噪声进行处理。根据光子散粒噪声变化的特点,将图像混有的噪声问题转化为求解一个多曝光图像序列组的平均值问题,合成的图像视觉效果与真实图像极为接近。     

Zn‐MOF‐74 Derived N‐Doped Mesoporous Carbon as pH‐Universal Electrocatalyst for Oxygen Reduction Reaction

It is of increasing importance to explore new low‐cost and high‐activity electrocatalysts for oxygen reduction reaction (ORR), which have had a substantial impact across a diverse range of energy conversion system, including various fuel cell and metal–air batteries. Although engineering carbon nanostructures have been widely explored as a candidate class of Pt‐based ORR electrocatalysts owing to their proved high activity, outstanding stability, and ease of use, there still remains a daunting challenge to develop high activity metal‐free electrocatalysts in pH‐universal electrolyte system. Here, a reliable and controllable route amenable to prepare nitrogen‐doped porous carbon (NPC) with high yields and exceptional quality is described. The as‐prepared NPC shows advantages of high activity, high durability, and methanol‐tolerant as an efficient pH‐universal electrocatalyst for ORR, showing comparable or even better activity as compared with the commercial Pt/C catalysts not only in alkaline media but also in acidic and neutral electrolyte. Systematic electrochemical studies, combining with density functional theory calculation, demonstrate the unique nitrogen‐doping species and favorable pores in the as‐designed NPC synergistically contribute to the significantly improved catalytic activity in pH‐universal medium. The present work potentially presents an important breakthrough in developing ORR electrocatalysts for various fuel cells.     

基于粗糙集的交通信号控制决策研究

粗糙集理论能够在分析大量经验数据基础上找到用于判断决策的规则,同时允许决策对象中存在一些不太完整的属性,并通过推理得出基本上确定的规则。将粗糙集理论与交通控制结合起来,对交通控制过程中的属性进行了分析,并将粗糙集理论的知识获取和决策分析算法应用到交通信号控制中,提出了一种系统的交通信号控制知识获取和决策的方法,是在解决城市交通状况决策问题上的一次有益的尝试。     

BALANCED TRUNCATED MODELS OF C INTERCONNECT CIRCUITS AND THEIR SIMULATION

The Balanced Truncation Method (BTM) is applied to an even distributed RC interconnect case by using Wang's closed-forms of even distributed RC interconnect models. The results show that extremely high order RC interconnect can be high-accurately approximated by only third order balanced model. Related simulations are executed in both time domain and frequency domain. The results may be applied to VLSI interconnect model reduction and design.     

基于改进Canny算子的手势图像边缘检测

针对手势检测不准确,手势边缘检测有偏差等问题,文中提出了一种改进的Canny算子用于检测手势图像边缘。改进的Canny算子使用自适应中值滤波与双边滤波相结合的方法去除图像噪声,并在Sobel的基础上扩展45°和135°方向的梯度幅值计算,自适应获取最佳阈值判别图像边缘。最后,使用哈夫变换与像素点的梯度方向相结合检测边缘,连接边缘、增强边缘。实验表明,改进后Canny算子检测的结果8连通数比传统Canny算子检测的结果8连通数多,边缘连续性较好,检测精度更高且自适应性增强。     

一种自适应维特比译码算法研究

在现代通信中,维特比译码是一种很好的纠错译码方法,对信道差错的控制,降低误码率,实现可靠通信有重要意义。然而随着译码约束长度的增加其实现的复杂度将会大大的增加。通过改进的维特比译码算法,在加比选模块时,设定一个门限和一个 N 值,计算每一步满足门限的路径数目,当其不满足与 N 值的关系时调整门限大小。这样每一状态选择最可能出现的若干条路径,从而减小当约束长度较大时译码的复杂度,实现快速译码。     

An innovative two-stage data compression scheme using adaptive block merging technique

Test data has increased enormously owing to the rising on-chip complexity of integrated circuits. It further increases the test data transportation time and tester memory. The non-correlated test bits increase the issue of the test power. This paper presents a two-stage block merging based test data minimization scheme which reduces the test bits, test time and test power. A test data is partitioned into blocks of fixed sizes which are compressed using two-stage encoding technique. In stage one, successive blocks are merged to retain a representative block. In stage two, the retained pattern block is further encoding based on the existence of ten different subcases between the sub-block formed by splitting the retained pattern block into two halves. Non-compatible blocks are also split into two sub-blocks and tried for encoded using lesser bits. Decompression architecture to retrieve the original test data is presented. Simulation results obtained corresponding to different ISCAS′89 benchmarks circuits reflect its effectiveness in achieving better compression.     

Robust L1-norm two-dimensional collaborative representation-based projection for dimensionality reduction

Collaborative representation-based projection (CRP) is a well-known dimensionality reduction technique, which has been proved to have better performance than sparse representation-based projection (SRP) in the fields of recognition and computer vision. However, classical CRP is sensitive to noises and outliers since its objective function is based on L2-norm, and it will suffer from the curse of dimensionality as it is used for images processing. In this paper, a novel CRP model, named L1-norm two-dimensional collaborative representation-based projection (L1-2DCRP) and an efficient iterative algorithm to solve it are proposed. Different from conventional CRP, the optimal problem in our proposed model is a L1-norm-based maximization and the vector data is extended to matrix date. The proposed algorithm is theoretically proved to be monotonously convergent, and more robust to noises and outliers since L1-norm is used. Experimental results on CMU Multi-PIE, COIL20, FERET and ORL face databases validate the effectiveness of L1-2DCRP compared with several state-of-the-art approaches.     

基于电磁降噪电路的恒流高清图像信号处理系统

本文设计了基于电磁降噪电路的恒流高清图像信号处理系统。系统中选用APW7120集成芯片作为中央处理芯片,以液晶显示器或智能终端显示屏作为显示单元,将信号滤波单元当作电子滤波器,据此,此系统可通过过滤图像信号内的干扰信号,优化图像信号质量;还可基于集成芯片直接简捷化系统结构,并控制系统自主生成的电磁噪声信号,以此保证系统在图像信号处理时不受电磁噪声影响,从而提高系统稳定性与可靠性;通过适度处理输入电流,可确保在正常运转时不会生成电磁干扰信号,以显著提升系统稳定性。