仪器的机壳电位及其对测试的影响

电子仪器大多采用三线电源线.当接通电源后,仪器的底座、面板、机箱等(统称为机壳)与插座中的大地线相接,使机壳保持为大地电位.但有不少电子仪器采用两线电源线.电源接通后,电源变压器的初级绕组两端分别与市电电源的相线和中线相联接,而机壳是浮置的.如果人体触及机壳,会有轻微的麻电感,用试电笔检测时氖管常会发亮.由此可说明机壳具有较高的对地电位.     

采用浮置接地电路以改善IHM失真

IHM(Interface Hum Modulation)失真,即接口交流声调制失真,是不久以前提出来的、主要发生在低频端的信号失真.本文主要介绍克服这种失真的具体措施——浮置接地法,即把电源电路对地浮置起来,使流过电源的大电流不致影响到信号端接地回路.     

CCD中的电荷泵效应

本文提出了一种CCD(电荷耦合器件)中的电荷泵效应。这种效应会引起FDR(浮置扩散区)的电位漂移,并带来一种特殊的电荷转移损失。当有电荷泵效应存在时,浮置扩散放大器就不是非破坏性电压读出。电荷泵效应可以用完全复位转移的办法加以消除。由此对FDR的复位深度提出了一个限制。     

新型浮栅MOS单管动态比较器设计

提出一种新型浮栅MOS单管动态比较器的电路结构。以浮栅MOS单管为核心,根据浮栅电荷的保持特性,在时钟控制下,两个电压分时地输入浮栅MOS管从而引起浮栅电位变化,相对变化后的浮栅电位决定着比较管的再通断,使预充电的输出电容与源极电容重新分配电荷,通过输出电容上电压是否发生变化来反映比较结果。单管比较避免差分对管由于工艺偏差所引起的输入失调问题,而且以浮栅偏置抵消MOS管的阈值。采用charted0.35μmCMOS工艺设计电路,面积约为0.003mm2,经前、后仿真和流片测试,结果表明,电路功能正确。并且在3.3V电源电压下、比较时间为0.4μs时,平均功耗为2.8mW。     

基于有源电容倍增器的新型电荷泵DC-DC变换器

电荷泵中浮置电容是影响输出特性的关键因素,针对大容量浮置电容难以集成的问题,提出利用电流传输器构成有源电容倍增器代替浮置电容的方法,可使等效的浮置电容容量提高1~3个数量级.利用PSPICE软件对反压及倍压电荷泵分别在采用有源电容倍增器和理想电容的情况下进行仿真,对比分析的结果说明采用有源电容倍增器的电荷泵电路仅需要很小的电容就能得到与外加大容量浮置电容电荷泵电路相同的输出特性(实例中100pF可等效50nF),从而基于有源电容倍增器的电荷泵将更易于全单片集成.     

一种改善三栅分栅快闪存储器耐久性能的方法

基于三栅分栅闪存在擦除操作F-N隧穿停止时界面电场恒定的特性,提出一种动态擦除电压模型,该模型基于稳定循环操作后浮栅电位的理念,通过实时可监测的浮栅电位值来动态调节闪存器件擦除操作的工作电压,提升了三栅分栅闪存器件的耐久特性.从实际监测数据可以看出,为保持稳定的浮栅电位,浮栅擦除操作电压随着编程/擦除循环次数先快速增加,并在循环10 000次后逐渐趋于饱和.相对于传统的恒擦除电压方式,通过这种新的动态擦除电压方式,器件在经过100 000次循环编程/擦除后阈值电压的漂移从原始1.2V降低为小于0.4V,优化了器件耐久性的工作窗口约0.8V.     

CF系列晶闸管触发器在整流、充电、浮充电电源中的应用

详细介绍了利用CF系列晶闸管触发器组成的自动稳压、稳流的整流(直流)电源、充电电源和电力操作用的浮充电电源的实例，同时还介绍了浮充电源的工作特性。     

具有单一集成电路特性的小巧、简便、高压电源

传感器、静电势阱和其它应用程序需要能传送适量输出电流的稳定高压电源。简单、低静态电流和小型化的电源是最合乎要求的。图1中的电路满足这些需求，其磁绝缘输出允许进行正极、负极或浮置输出的配置。     

新型电路元件PVI的内部原理及应用

美国国际整流器公司的光电隔离器可认为是一种电流控制浮置恒压源，其输出电流和输入电流成线性关系。是一种具有革命意义的新型元件，通过ＰＶＩ的并联和串接，可大大简化现有ＭＯＳＦＥＴ的高端驱动，浮动电源，线性电源，变换器，光耦合器，信号隔离器，Ｉ－Ｄ接口等种种电路。     

单个浮置场限环终端结构击穿电压模型

基于B.J.Baliga的击穿电压理论,通过求解双边突变圆柱结的泊松方程,提出了单个浮置场限环终端结构的击穿电压解析模型.该模型计算结果与模拟结果的误差在±7%之内,具有精度高、应用范围广等特点,可以帮助设计者初步确定浮置场限环注入窗口大小及与主结的间距等关键参数.     

基于Radon变换的昆虫上升下降率提取算法及实验验证

昆虫上升下降率是反映昆虫在迁飞过程中的运动方向与运动速率的重要指标。由于传统垂直昆虫雷达存在距离分辨率低、目标检测关联算法不完善等问题,昆虫上升下降率的提取较为复杂。本文提出一种基于Radon变换的昆虫上升下降率提取算法,该算法通过脉冲多普勒积累与恒虚警检测实现了雷达快时间/慢时间一维距离像矩阵到二值化航迹矩阵的转换,再利用Radon变换从二值化航迹矩阵中实现了昆虫上升下降率的直接提取。通过对实测数据的处理,验证了该算法的可行性。      

Image recovery using partitioned-separable paraboloidal surrogatecoordinate ascent algorithms

Iterative coordinate ascent algorithms have been shown to be useful for image recovery, but are poorly suited to parallel computing due to their sequential nature. This paper presents a new fast converging parallelizable algorithm for image recovery that can be applied to a very broad class of objective functions. This method is based on paraboloidal surrogate functions and a concavity technique. The paraboloidal surrogates simplify the optimization problem. The idea of the concavity technique is to partition pixels into subsets that can be updated in parallel to reduce the computation time. For fast convergence, pixels within each subset are updated sequentially using a coordinate ascent algorithm. The proposed algorithm is guaranteed to monotonically increase the objective function and intrinsically accommodates nonnegativity constraints. A global convergence proof is summarized. Simulation results show that the proposed algorithm requires less elapsed time for convergence than iterative coordinate ascent algorithms. With four parallel processors, the proposed algorithm yields a speedup factor of 3.77 relative to single processor coordinate ascent algorithms for a three-dimensional (3-D) confocal image restoration problem.     

Grouped-coordinate ascent algorithms for penalized-likelihoodtransmission image reconstruction

Presents a new class of algorithms for penalized-likelihood reconstruction of attenuation maps from low-count transmission scans. We derive the algorithms by applying to the transmission log-likelihood a version of the convexity technique developed by De Pierro for emission tomography. The new class includes the single-coordinate ascent (SCA) algorithm and Lange's convex algorithm for transmission tomography as special cases. The new grouped-coordinate ascent (GCA) algorithms in the class overcome several limitations associated with previous algorithms. (1) Fewer exponentiations are required than in the transmission maximum likelihood-expectation maximization (ML-EM) algorithm or in the SCA algorithm. (2) The algorithms intrinsically accommodate nonnegativity constraints, unlike many gradient-based methods. (3) The algorithms are easily parallelizable, unlike the SCA algorithm and perhaps line-search algorithms. We show that the GCA algorithms converge faster than the SCA algorithm, even on conventional workstations. An example from a low-count positron emission tomography (PET) transmission scan illustrates the method     

A note on convergence problems in numerical techniques foraccelerated life-testing analysis

Numerical solutions to determine maximum-likelihood estimators of parameters use a variety of techniques such as Newton-Raphson, Hook-Jeeves, and steepest ascent. All of these methods are subject to convergence difficulties that frequently occur in simulation studies. A tested and tried transformation for a variety of likelihood functions, and for the above mentioned numerical techniques, is introduced. The transformation is recommended for situations in which convergence difficulties are encountered     

旋转法下降炉的智能控制

随着我国人工晶体材料工业的飞速发展,急需性能优良、稳定性好、自动化程度高的晶体生长设备。提出了炉室上升坩埚旋转技术,不仅利于提高生长晶体的品质,而且生长设备简单,易于实现自动化控制。采用性能优良的ADμC812微控制芯片进行控制．是晶体生长设备控制方法的有益探索。该设备自动化程度较高,速度运行可靠,维护简单方便,具有推广价值。     

LAS Detector with Soft-Output MMSE Initialization Under Imperfect Channel Estimation and Channel Correlation

Wireless Personal Communications - This paper proposes a modified likelihood ascent search (LAS) algorithm for multiple-input multiple-output (MIMO) systems under correlated channel and imperfect...     

On the convergence of the generalized maximum likelihood algorithmfor nonuniform image motion estimation

The generalized maximum likelihood algorithm is a powerful iterative scheme for waveform estimation. This algorithm seeks for the maximum likelihood estimates of the Karhunen-Loeve expansion coefficients of the waveform. The search for the maximum is performed by the steepest ascent routine. The objective of the paper is to obtain conditions that assure the stability in the mean for frame-to-frame image motion estimation. Sufficient conditions are established for the convergence of the algorithm in the absence of noise. Experimental results are presented that illustrate the behavior of the algorithm in the presence of various noise levels.     

Experimental investigation of an adaptive feedback algorithm forhot spot reduction in radio-frequency phased-array hyperthermia

A computer-controlled adaptive phased array radiofrequency hyperthermia system for improved therapeutic tumor heating is experimentally investigated. Adaptive array feedback techniques are used to modify the electric-field in hyperthermia experiments with a homogeneous saline phantom target. A hyperthermia phased-array antenna system has been modified to implement adaptive nulling and adaptive focusing algorithms. The hyperthermia system is a ring phased-array antenna applicator with four independently controlled RF transmitter channels operating at a CW frequency of 100 MHz. The hyperthermia phased array is made adaptive by software modifications which invoke a gradient-search feedback algorithm that controls the amplitude and phase of each transmitter channel. The gradient-search algorithm implements the method of steepest descent for adaptive nulling (power minimization) and the method of steepest ascent for adaptive focusing (power maximization). The feedback signals are measured by electric-field short-dipole probe antennas. The measured data indicate that with an adaptive hyperthermia array it may be possible to maximize the applied electric field at a tumor position in a complex scattering target body and simultaneously minimize or reduce the electric field at target positions where undesired high-temperature regions (hot spots) occur     

A generalized EM algorithm for 3-D Bayesian reconstruction from Poisson data using Gibbs priors

A generalized expectation-maximization (GEM) algorithm is developed for Bayesian reconstruction, based on locally correlated Markov random-field priors in the form of Gibbs functions and on the Poisson data model. For the M-step of the algorithm, a form of coordinate gradient ascent is derived. The algorithm reduces to the EM maximum-likelihood algorithm as the Markov random-field prior tends towards a uniform distribution. Three different Gibbs function priors are examined. Reconstructions of 3-D images obtained from the Poisson model of single-photon-emission computed tomography are presented.     

Analysis of pulse dispersion distortion along exponential andChebyshev microstrip tapers

The voltage and current transfer functions are shown for the tapered line. The dispersion distortion obtained by using these transfer functions are shown for the nonideal square pulse along the exponential taper and the Chebyshev taper. The great and sharp peak in the front of the distorted wave is caused due to the frequency dispersive characteristics of effective relative permittivity. The sustained tail and the ascent of gentle slope in the plateau in the distorted wave are caused due to the multi-reflection in the tapered line and are inherent characteristics in the configuration of taper. The sustained tail starts to vanish after the time of about one and half times of the echo time