电容式绝对压力传感器的改进模型及温度特性分析

在传感器敏感膜模型的基础上对电容式绝对压力传感器提出了一种改进模型,考虑了由于温度的变化电容结构空腔中残余气体对传感器性能产生的影响.结果表明温度的改变会导致残余气体压力的改变,进而使传感器的测量产生一定的温度漂移,同时也降低了传感器的灵敏度;并由此计算了残余气体存在时,传感器测量值的温度漂移量以及灵敏度的温度系数.这对于工艺的改进以及后续电路的设计具有指导意义.     

城域传送网设备技术发展及要求

本文通过对城域传送网设备的技术分析,阐述了SDH设备、第一代MSTP设备、第二代MSTP设备在技术上的缺陷,描述了目前工程建设中城域传送网对MSTP设备的SDH功能要求和以太网功能要求,特别是对以太网封装、虚级联、链路容量调整、内嵌式RPR、内嵌式MPLS的技术要求.     

全保偏M-Z型光纤磁场传感系统实验研究

报道一种基于全保偏Mach Zender型干涉检测的光纤磁场传感系统。采用TbDyFe磁致伸缩材料,在长度约为10cm的裸保偏光纤上环绕了一层厚度约为2μm的膜,大大提高了磁致伸缩材料与光纤的附着性能,解决了光纤弯曲问题。选用保偏光纤耦合器、保偏光纤偏振器,构成包括传感部分在内的全部保偏的Mach Zender型光纤传感系统,从根本上抑制了系统偏振噪声;利用主动相位补偿法有效地消除了干涉仪系统的相位漂移。对系统的直流偏置和交流磁场响应特性进行了测试。实验结果表明,系统的相位随磁场变化的灵敏度为0.45458rad/mT,可检测的磁场分辨率达到2×10-8T。     

语音信号互信息估计的非线性搜索算法及识别应用

基于互信息理论的语音识别方法不仅考虑了语音信号的时变分布特征，并且考虑了语音信号的统计分布特征，能有效地提高同类模式的凝聚度，减少非同类模式间的耦合性，在语音识别实验和实际应用中反映出良好的识别精度和很高的运行效率，与其它方法相比更适合嵌入式系统的语音识别应用。本文提出了一种互信息估计的非线性搜索算法，这一算法能够有效地处理语音信号时变分布特征的非线性波动，进一步提高语音模式互信息匹配的精度。     

Rate Control Algorithm Considering Mobility in Mobile Ad Hoc Networks

For reducing the loss of data packet due to network congestion and mobility, rate control algorithm is effective means for ensuring the fair allocation of network resource among communication flows and alleviating network congestion. The Transport Control Protocol (TCP) was originally designed for wire-line networks, where the links are assumed to be reliable and with fixed capacities. However, the performance of TCP becomes very poor when it is directly used in ad hoc networks. Some optimization-based congestion control schemes have been proposed to improve TCP performance in ad hoc networks, but the mobility of hosts and route change frequently are not considered for designing rate control algorithm. In this paper, we propose rate control algorithms in a more practical way by taking into account link congestion and node movement. Numerical results show that the rate control algorithms can approach the globally optimal value and show the effect of the node mobility on the algorithms.     

A novel multicast routing algorithm in sparse splitting WDM network with power attenuation constraint

With the increasing requirement for communication bandwidth, all-optical network has been more and more important owning to its large traffic capability. Multicasting is an important technology in wavelength division multiplexing (WDM) optical network, and has been studied in many works. In this paper, we consider the multicasting technology on all-optical metropolitan area network (MAN) with maximum power attenuation constraint. The objective is to minimize total cost of a multicasting request. This problem is NP-hard. We propose a heuristic, named Power-Constraint Fix-Destination-Path (PC-FDP) algorithm, to solve this maximal power-loss constrained minimizing cost multicasting problem. It means that, during the process of building a multicasting tree, when a destination is reached and its power satisfies the constraint, the path from source to it would be fixed in the tree. Simulation results show that, all multicasting trees building the proposed algorithm satisfy the power constraint, with slight increasing of the total cost.     

移动终端桌面发展新趋势

对移动终端桌面增值业务进行了研究,简要介绍移动终端桌面业务概念,重点叙述移动终端桌面系统构成以及组成部分的功能,并给出业务的运行环境和一些流程示例,最后对业务实施提出几点建议。     

1.25～3.125 Gb/s连续数据速率CDR设计

设计了一款工作速率为1.25～3.125 Gb/s的连续可调时钟数据恢复(CDR)电路,可以满足多种通信标准的设计需求.CDR采用相位插值型双环路结构,使系统可以根据应用需求对抖动抑制和相位跟踪能力独立进行优化.针对低功耗和低噪声的需求,提出一种新型半速率采样判决电路,利用电流共享和节点电容充放电技术,数据速率为3.125 Gb/s时,仅需要消耗50 μA电流.芯片采用0.13 μm工艺流片验证,面积0.42 m㎡,功耗98 mw,测试结果表明,时钟数据恢复电路接收PRBS7序列时,误码率小于10-12.     

Human identification using finger images

This paper presents a new approach to improve the performance of finger-vein identification systems presented in the literature. The proposed system simultaneously acquires the finger-vein and low-resolution fingerprint images and combines these two evidences using a novel score-level combination strategy. We examine the previously proposed finger-vein identification approaches and develop a new approach that illustrates it superiority over prior published efforts. The utility of low-resolution fingerprint images acquired from a webcam is examined to ascertain the matching performance from such images. We develop and investigate two new score-level combinations, i.e., holistic and nonlinear fusion, and comparatively evaluate them with more popular score-level fusion approaches to ascertain their effectiveness in the proposed system. The rigorous experimental results presented on the database of 6264 images from 156 subjects illustrate significant improvement in the performance, i.e., both from the authentication and recognition experiments.     

Abrupt motion tracking via intensively adaptive Markov-chain Monte Carlo sampling

The robust tracking of abrupt motion is a challenging task in computer vision due to its large motion uncertainty. While various particle filters and conventional Markov-chain Monte Carlo (MCMC) methods have been proposed for visual tracking, these methods often suffer from the well-known local-trap problem or from poor convergence rate. In this paper, we propose a novel sampling-based tracking scheme for the abrupt motion problem in the Bayesian filtering framework. To effectively handle the local-trap problem, we first introduce the stochastic approximation Monte Carlo (SAMC) sampling method into the Bayesian filter tracking framework, in which the filtering distribution is adaptively estimated as the sampling proceeds, and thus, a good approximation to the target distribution is achieved. In addition, we propose a new MCMC sampler with intensive adaptation to further improve the sampling efficiency, which combines a density-grid-based predictive model with the SAMC sampling, to give a proposal adaptation scheme. The proposed method is effective and computationally efficient in addressing the abrupt motion problem. We compare our approach with several alternative tracking algorithms, and extensive experimental results are presented to demonstrate the effectiveness and the efficiency of the proposed method in dealing with various types of abrupt motions.