Tailored wafer holder for a reliable deposition of sputtered aluminium nitride thin films at low temperatures

Active actuated resonant micro-electro-mechanical-systems (MEMS) are used for sensing purpose like topography analysis and viscosity sensors. Those applications require straight beams and they rely on controlled film stress of the involved thin films, e.g. the active piezoelectric aluminium nitride (AlN) layer. The AlN consists of aluminium and nitrogen and is deposited with a reactive sputter process. The deposition process heats up the substrate and therefore the wafer bow of the substrate causes a variation of the thermal connection between wafer and sample holder. This goes along with undefined film stress of the AlN layer. In order to minimize the derivation of film stress, the reduction of substrate temperature and the enhancement of thermal connection between substrate and substrate holder is targeted. Therefore a novel clamped substrate holder is designed. High thermal connection to the ambient equipment, equal heat distribution and clamping of wafer stabilize the deposited AlN layer. By examining the layer stress and applying an acid structuring method, an improvement of deposited film is observed. A long term study with AlN deposition with thicknesses of 0.5 µm, 1.0 µm and 2.0 µm on silicon wafers was made to confirm the enhancement.     

单臂压缩感知鬼成像的光强扩散函数分析法

为了提高单臂压缩感知鬼成像的成像质量,减少成像系统本身和外部环境的干扰,提出了一种光强扩散函数分析方法.在单臂压缩感知鬼成像原理的基础上分析了成像过程,指出降低成像质量的主要因素是菲涅尔衍射和大气湍流.针对这两个因素,推导并分析了光强度扩散函数的公式,研究透镜的焦距与口径之比和照明光源的波长对鬼成像的影响.仿真结果表明:在单臂压缩感知鬼成像中,使用焦距与尺寸半径之比在2~5范围内的成像投影透镜可以消除衍射效应的影响;短波长光源适用于大气湍流较弱时的成像,长波长光源在大气湍流较强时对干扰有更好的耐受能力.该方法可以有效地提高成像质量并优化成像系统.     

Opening and contact zones of an interface crack in a piezoelectric bimaterial under combined compressive-shear loading

A plane problem for a tunnel electrically permeable interface crack between two semi-infinite piezoelectric spaces is studied. A remote mechanical and electrical loading is applied. Elastic displacements and potential jumps as well as stresses and electrical displacement along the interface are presented using a sectionally holomorphic vector function. It is assumed that the interface crack includes zones of crack opening and frictionless contact. The problem is reduced to a combined Dirichlet–Riemann boundary value problem which is solved analytically. From the obtained solution, simple analytical expressions are derived for all mechanical and electrical characteristics at the interface. A quite simple transcendental equation, which determines the point of separation of open and close sections of the crack, is found. For the analysis of the obtained results, the main attention is devoted to the case of compressive-shear loading. The analytical analysis and numerical results show that, even if the applied normal stress is compressive, a certain crack opening zone exists for all considered loading values provided the shear field is present. It is found that the shear stress intensity factor at the closed crack tip and the energy release rates at the both crack tips depend very slightly on the magnitude of compressive loading.     

Alumina/Polyimide Composite Porous Nanosolid: Dielectric Characteristics and Compressive Strength

Al₂O₃ porous nanosolid was prepared via solvothermal hot-press(SHP) method. The dielectric constant of Al₂O₃ porous nanosolid is as low as 2.34, while its compressive strength is very poor. In order to improve the compressive strength and maitain low dielectric constant, polyimide was introduced to prepare Al₂O₃/polyimide composite porous nanosolid. Compared to Al₂O₃ porous nanosolid, Al₂O₃/polyimide composite porous nanosolid possesses much higher compressive strength, which reaches its saturation value when the mass loading of polyimide is 7.75%. In addition, the in situ Fourier transformation infrared(FTIR) monitoring result reveals that Al₂O₃/polyimide composite porous nanosolid is stable up to 400℃.     

分布式压缩感知实现联合信道估计的方法

针对无线通信中多个信道之间存在相关性的现象,本文研究了基于压缩感知的联合信道估计。通过选取多个节点与簇头之间的信道为研究背景,本文建立了多信道下的联合信道估计模型,推导了判决门限与信噪比之间的关系,提出了基于门限自适应-正交匹配追踪联合重构技术(TA-SOMP)的信道估计算法,并进行了相应的仿真实验。仿真结果表明:与经典的正交匹配追踪(OMP)算法相比,本文算法所重构的信道与原始信道之间的均方误差(MSE)更小,传输信号误比特率(BER)更低;在相同信噪比环境下,TA-SOMP算法所需导频数量更少,频带利用率更高。      

A fast converging sparse reconstruction algorithm in ghost imaging

A fast converging sparse reconstruction algorithm in ghost imaging is presented. It utilizes total variation regularization and its formulation is based on the Karush-Kuhn-Tucker (KKT) theorem in the theory of convex optimization. Tests using experimental data show that, compared with the algorithm of Gradient Projection for Sparse Reconstruction (GPSR), the proposed algorithm yields better results with less computation work.     

Bayesian compressive sensing for cluster structured sparse signals

In traditional framework of compressive sensing (CS), only sparse prior on the property of signals in time or frequency domain is adopted to guarantee the exact inverse recovery. Other than sparse prior, structures on the sparse pattern of the signal have also been used as an additional prior, called model-based compressive sensing, such as clustered structure and tree structure on wavelet coefficients. In this paper, the cluster structured sparse signals are investigated. Under the framework of Bayesian compressive sensing, a hierarchical Bayesian model is employed to model both the sparse prior and cluster prior, then Markov Chain Monte Carlo (MCMC) sampling is implemented for the inference. Unlike the state-of-the-art algorithms which are also taking into account the cluster prior, the proposed algorithm solves the inverse problem automatically—prior information on the number of clusters and the size of each cluster is unknown. The experimental results show that the proposed algorithm outperforms many state-of-the-art algorithms.     

Regularized signal reconstruction for level-crossing sampling using Slepian functions

In this paper, we propose a method for efficient signal reconstruction from non-uniformly spaced samples collected using level-crossing sampling. Level-crossing (LC) sampling captures samples whenever the signal crosses predetermined quantization levels. Thus the LC sampling is a signal-dependent, non-uniform sampling method. Without restriction on the distribution of the sampling times, the signal reconstruction from non-uniform samples becomes ill-posed. Finite-support and nearly band-limited signals are well approximated in a low-dimensional subspace with prolate spheroidal wave functions (PSWF) also known as Slepian functions. These functions have finite support in time and maximum energy concentration within a given bandwidth and as such are very appropriate to obtain a projection of those signals. However, depending on the LC quantization levels, whenever the LC samples are highly non-uniformly spaced obtaining the projection coefficients requires a Tikhonov regularized Slepian reconstruction. The performance of the proposed method is illustrated using smooth, bursty and chirp signals. Our reconstruction results compare favorably with reconstruction from LC-sampled signals using compressive sampling techniques.     

超宽带信道建模中基于压缩感知的解卷积算法

针对频域测量方式下的超宽带(UWB)信道测量数据后处理,该文提出了用具有高斯滚降特性过渡带的类高斯窗,提取符合中国UWB频谱规范的信道测量数据,并将类高斯窗对应的时域脉冲作为先验信息,使用基于压缩感知(CS)的算法对时域信道测量信号解卷积,使得解卷积后的信道冲激响应具有高分辨率特性。利用频域加窗补零,以及改变解卷积算法中参数化波形字典原子的步长,可以得到不同分辨率的解卷积结果。采用匹配追踪(Matching Pursuit,MP)算法作为CS的重构算法。针对一间办公室的视距(LOS)与非视距(NLOS)信道测量数据处理结果表明,基于压缩感知的解卷积算法可以用较少的观测值获得和CLEAN算法相近的解卷积性能。