无线多中继系统中判决门限辅助的快速Z转发协作

针对Z向转发(ZF)协作所有中继节点均参与协作转发导致的能耗利用不合理问题, 该文提出了一种适用于多中继场景下的门限辅助判决快速Z转发(DT-FZF)协作.当中继节点处接收信号对数似然比(LLR)的绝对值小于门限时,中继节点不参与协作转发;否则中继节点协作转发经截断后的对数似然比(LLR).放大转发(AF)、译码转发(DF)、分段转发(PF)和ZF协作可看作DT-FZF协作的特殊情况.在三中继系统,误比特率(BER)为10–3时,相比ZF协作,所提协作可获得约0.8 dB的性能增益.     

W波段64通道相控阵微系统设计与实现

相控阵微系统的主要特征是电路与天线的高度融合集成,将三维微纳集成技术和微电子技术紧密地结合在一起,切合相控阵高频化、小型化和低成本的发展需求。本文设计了一款W波段的封装天线相控阵微系统,该相控阵采用硅基三维集成的方式将T/R多功能芯片、天线阵列集成在一个微系统模块中,并详细介绍了基于硅工艺的多功能收发芯片设计和相控阵封装天线设计。给出了相控阵微系统的测试结果。该微系统具有高集成度、高性能、低成本的特点,可以为高速无线通信、高精度探测和成像等应用提供一个较优的技术路径。     

锑化铟抛光片表面粗糙度优化研究

锑化铟是中波红外探测应用较广的材料。抛光片的表面粗糙度是影响器件性能的关键指标。研究了锑化铟化学机械抛光(Chemical Mechanical Polishing, CMP)液的pH值、氧化剂比例以及抛光液流速对锑化铟抛光片表面粗糙度的影响,并结合原子力显微镜(Atomic Force Microscope, AFM)和表面轮廓仪测试对抛光片的表面粗糙度进行了表征和优化。结果表明,当pH值为8、氧化剂比例为0.75%、抛光液流速为200 L/min时,InSb晶片的表面粗糙度为1.05 nm (AFM),同时晶片的抛光宏观质量较好。     

基于智能手机平台的计算光学显微成像技术研究综述

计算光学显微成像技术将光学编码和计算解码相结合,通过光学操作和图像算法重建来恢复微观物体的多维信息,为显微成像技术突破传统成像能力提供了强大的助力。这项技术的发展得益于现代光学系统、图像传感器以及高性能数据处理设备的优化,同时也被先进的通信技术和设备的发展所赋能。智能手机平台作为高度集成化的电子设备,具有先进的图像传感器和高性能的处理器,可以采集光学系统的图像并运行图像处理算法,为计算光学显微成像技术的实现创造了全新的方式。进一步地,作为可移动通信终端,智能手机平台开放的操作系统和多样的无线网络接入方法,赋予了显微镜灵活智能化操控能力与丰富的显示和处理分析功能,可用于实现各种复杂环境下多样化的生物学检测应用。文中从四个方面综述了基于智能手机平台的计算光学显微成像技术,首先综述了智能手机平台作为光学成像器件的新型显微成像光路设计,接下来介绍了基于智能手机平台先进传感器的计算光学高通量显微成像技术,然后介绍了智能手机平台的数据处理能力和互联能力在计算显微成像中的应用,最后讨论了这项技术现存在的一些问题及解决方向。     

基于多元高斯混合模型的离线指纹数据库

针对室内环境下单次采样测量值的波动变化及信号间的相互干扰,该文提出一种基于分区多元高斯混合模型(MVGMM)的室内定位系统.根据信号接入点(AP)铺设位置与空间结构,系统采用一对多支持向量机算法对目标区域做分区操作,以精确信号变化的区域范围.利用狭小分区内信号间的耦合关系,建立基于信号间相互干扰的多元高斯混合模型,以改善信号波动所造成的定位精度下降.当室内环境发生变化时,基于分区多元高斯混合模型的自适应更新算法可对各分区指纹数据的可信度做出判断,并以自适应算法更新信号波动较大分区的模型参数,提高模型与现有环境间的耦合程度.实验结果表明,该文算法可利用相对少量样本数据,构建稳定可维护的室内信号分布模型,相较于其他算法,其定位精度也有一定程度提高.     

Metal Micropatterning by Triboelectric Spark Discharge

Metal micropatterns play critical roles in flexible electronics. However, the lack of versatile strategies for micropatterning of diverse metal materials on various thin, flexible or stretchable substrates has limited the rapid development of flexible electronics. Here, a metal micropatterning method by triboelectric spark discharge under atmospheric environment is developed, where a triboelectric nanogenerator (TENG) is employed to precisely and safely control the voltage, current, and frequency of the spark discharges. Micropatterns of metal films like gold, silver, copper, aluminum and platinum are successfully fabricated on substrates of polyimide, polyethylene terephthalate, polyvinyl chloride, polydimethylsiloxane, paper or latex, even on ultrathin substrates (5 μm thick) without damage, where the feature sizes of metal patterns are controllable from 20 μm to 1 mm. Experimental insights into the triboelectric spark discharge behaviors and the pattern feature sizes control are discussed. A straightforward fabrication of metal patterns on the balloon surface or human skin through “handwriting” by a pencil as discharge electrode is realized. Besides metals, extended processibility of conductive materials like carbon nanotubes, graphene, MXene, graphite, carbon fibers, and conductive polymers are also demonstrated. This work proves the possibility of microfabrication by TENG, which is of simplicity and attractiveness for flexible electronics.     

Infrared target tracking based on proximal robust principal component analysis method

Applied Intelligence - Infrared target tracking plays an important role in both civil and military fields. The main challenges in designing a robust and high-precision tracker for infrared...     

Intelligent wavelet fuzzy brain emotional controller using dual function-link network for uncertain nonlinear control systems

This study aims to propose a more efficient hybrid algorithm to achieve favorable control performance for uncertain nonlinear systems. The proposed algorithm comprises a dual function-link network-based multilayer wavelet fuzzy brain emotional controller and a sign(.) functional compensator. The proposed algorithm estimates the judgment and emotion of a brain that includes two fuzzy inference systems for the amygdala network and the prefrontal cortex network via using a dual-function-link network and three sub-structures. Three sub-structures are a dual-function-link network, an amygdala network, and a prefrontal cortex network. Particularly, the dual-function-link network is used to adjust the amygdala and orbitofrontal weights separately so that the proposed algorithm can efficiently reduce the tracking error, follow the reference signal well, and achieve good performance. A Lyapunov stability function is used to determine the adaptive laws, which are used to efficiently tune the system parameters online. Simulation and experimental studies for an antilock braking system and a magnetic levitation system are presented to verify the effectiveness and advantage of the proposed algorithm.

     

融合深度学习与成像模型的水下图像增强算法

水下机器人的视觉感知功能因受到水下环境因素的影响,面临着图像质量降低的挑战,如图像颜色畸变、整体色调偏绿、偏蓝、对比度较低、细节较为模糊等。提出一种结合深度学习方法与物理成像模型的新型水下图像增强算法,通过构建包含扩张卷积和带参数激活函数的神经网络,进行背景散射光和直接传输映射的估计,并结合成像模型的数学表达进行重建运算得到增强后图像。实验结果表明,与UDCP、IBLA、GLNet等典型图像增强算法相比,该算法具有更快的运算速度,且能够消除水下环境因素带来的影响,丰富图像色彩的同时能增强各类细节,在峰值信噪比指标和结构相似度指标上取得了较大值。此外,增强后的图像在特征点匹配实验中获得了更好的匹配效果。