FBP平面凸点式封装

1、产品及其简介平面凸点式封装(FBP)体积小,功能优,目前最小的封装尺寸已可以做到0.8mm*0.6mm*0.4mm,独特的凸点镀金式引脚使表面安装技术(SMT)焊接更为方便可靠。FBP封装可以适应共晶、导电胶、软焊料等不     

新型的半导体封装形式FBF

平面凸点式封装FBP（Flat Bump Package）是一种新型的封装形式．它是针对目前QFN（Quad Flat No-lead）在封装工艺中一些无法根本解决问题而重新选择的设计方案。     

平面凸点式封装(FBP)

QFN工艺(Quad Flat No-lead)在封装过程中大多存在着焊线牢度不够、包封溢胶、切 割毛刺等缺陷,FBP(Flat Bump Package)的出现不仅很好地解决了QFN的缺陷,而且FBP产品 在SMT工艺中能表现出更优良的特性。文章主要介绍了FBP的设计思路、结构特点、主要工艺流 程、关键工艺和衍生产品等。     

长电科技展示新型封装技术FBP

<正>在前不久落下帏幕的“中国集成电路产业发展研讨会暨第八界中国半导体行业协会集成电路分会年会”上,江苏长电科技股份有限公司向业界展示了其自主研发的新型封装技术FBP (Flat Bump Package)。     

本土IC封测业面临的挑战

2006年中国大陆封测业销售额496．6亿元,比2005年增长了44％,占2006年中国IC产业销售额的50．8％,未达到国际公认的设计业：制造业：封测业=30％：40％：30％的要求。目前大陆IC封装以中低端DIP、SOP（SSOP、TSOP）、QFP（LQFP、TQFP）为主,正在向高附加值、多引脚数QFP、MCM（MCP）、BGA、CSP、SiP、PiP、PoP等中高端封装过渡。近年来,本土封装在技术上的某些领域有所突破,如江阴长电FBP、南通富士通MCM（MCP）、BGA、中电科技第13所CBGA等,但是仍面临着全球IC大厂、IC封测厂、产能、技术和人才等多方面的挑战,只有正视这些挑战,采取积极措施,克服弊端,才能进步。文章最后得出结论,未来5年,中国IC封测业有可能成为全球最大的半导体封测基地。     

第二届中国半导体企业领军人物

王国平华润微电子(控股)有限公司董事、总经理面对激烈的市场竞争,他率领的华润微电子,全面推进国企转型,开发多种新工艺并批量生产新品197个,高效率、低成本完成6英寸线建设,多项经济指标创造历史新高,2005年,营业收逾21.8亿港元,利润总额1.8亿港元。王新潮江苏长电科技股份有限公司董事长他广搅人才、勇于进取,在他带领下的长电科技公司经营指标持续高速增长,公司大范围调整产品工艺结构,推出有自主知识产权的FBP(平面凸点式)封闭,实现向以中高档封装为主的转变,下属长电先进公司成立短短两年成为国际上第4家拥有圆片级封装及芯片凸块技…     

超宽带线性调频信号快速BP成像

首先对超宽带线性调频信号进行脉冲压缩处理得到短脉冲信号，在详细阐述BP算法原理的基础上，利用此短脉冲信号推导其BP算法成像公式；然后将子孔径思想应用于BP算法，得到一种快速BP(FBP)算法；最后对BP算法和FBP算法的计算量进行理论分析，同时结合点目标和多点目标应用BP算法和FBP算法分别成像，给出两种算法成像所花费的时间，其结果证明了FBP算法的快速性和有效性。     

脉冲探地雷达的快速BP算法

基于脉冲探地雷达的后向投影（back-projection,BP）成像算法在处理大宗数据时由于运算量大而使得计算效率较低。文中在传统BP算法的基础上提出了一种快速后向投影（fast back-projection,FBP）成像算法,并以单个点目标和多个点目标的成像为例,将该算法应用于脉冲探地雷达的成像,其计算效率较传统的BP算法有显著提高,而且理论推导和仿真结果均表明,FBP算法的成像质量与传统BP算法相近,从而得出了FBP算法的优越性。     

基于FBP的迭代算法研究

在用传统的滤波反投影算法（FBP）重建图像时,往往不可避免地出现许多伪影。为了减少伪影,论述了一种基于FBP的迭代算法,此处投影采用平行光束。算法分为三个过程,第一个过程采用FBP算法重建图像,第二个过程将重建后的图像再次投影并与第一次的投影做外差并将此差值做反投影获得改进量,第三个过程将改进量与第一次重建的图像相加获得修正后的图像,重复该过程。多次迭代后图像膺像明显减少,图像质量增强。     

基于压缩感知的加速前向后向匹配追踪算法

前向后向匹配追踪(FBP)算法作为一个新颖的两阶段贪婪逼近算法,因为较高的重构精度和不需要稀疏度作为先验信息的特点,受到了人们的广泛关注。然而,FBP算法必须运行更多的时间才能得到更高的精度。鉴于此,该文提出加速前向后向匹配追踪(AFBP)算法。该算法利用每次迭代中候选支撑集的信息,实现对已删除原子的再次加入,以此减少算法迭代次数。通过不同非零项分布的稀疏信号和稀疏图像的仿真结果表明,相对于FBP算法,该文提出的方案在不降低重构精度的同时,大幅降低了算法运行时间。     

Reducing negativity artifacts in emission tomography: post-processing filtered backprojection solutions

The problem of negative artifacts in emission tomography reconstructions computed by filtered backprojection (FBP) is of practical concern particularly in low count studies. Statistical reconstruction methods based on maximum likelihood (ML) are automatically constrained to be non-negative but their excessive computational overhead (orders of magnitude greater than FBP) has limited their use in operational settings. Motivated by the statistical character of the negativity artifact, the authors develop a simple post-processing technique that iteratively adjusts negative values by cancellation with positive values in a surrounding local neighborhood. The compute time of this approach is roughly equivalent to 2 applications of FBP. The approach was evaluated by numerical simulation in 1- and 2-dimensional (2D) settings. In 2D, the source distributions included the Hoffman, the Shepp and Vardi, and a digitized version of the Jaszczak cold spheres phantoms. The authors' studies compared smoothed versions of FBP, the post-processed FBP, and ML implemented by the expectation-maximization algorithm. The root mean square (RMS) error between the true and estimated source distribution was used to evaluate performance; in 2D, additional region-of-interest-based measures of reconstruction accuracy were also employed. In making comparisons between the different methods, the amount of smoothing applied to each reconstruction method was adapted to minimize the RMS error-this was found to be critical.     

Penalized maximum likelihood reconstruction for improved microcalcification detection in breast tomosynthesis

We examined the application of an iterative penalized maximum likelihood (PML) reconstruction method for improved detectability of microcalcifications (MCs) in digital breast tomosynthesis (DBT). Localized receiver operating characteristic (LROC) psychophysical studies with human observers and 2-D image slices were conducted to evaluate the performance of this reconstruction method and to compare its performance against the commonly used Feldkamp FBP algorithm. DBT projections were generated using rigorous computer simulations that included accurate modeling of the noise and detector blur. Acquisition dose levels of 0.7, 1.0, and 1.5 mGy in a 5-cm-thick compressed breast were tested. The defined task was to localize and detect MC clusters consisting of seven MCs. The individual MC diameter was 150 μm. Compressed-breast phantoms derived from CT images of actual mastectomy specimens provided realistic background structures for the detection task. Four observers each read 98 test images for each combination of reconstruction method and acquisition dose. All observers performed better with the PML images than with the FBP images. With the acquisition dose of 0.7 mGy, the average areas under the LROC curve (A(L)) for the PML and FBP algorithms were 0.69 and 0.43, respectively. For the 1.0-mGy dose, the values of A(L) were 0.93 (PML) and 0.7 (FBP), while the 1.5-mGy dose resulted in areas of 1.0 and 0.9, respectively, for the PML and FBP algorithms. A 2-D analysis of variance applied to the individual observer areas showed statistically significant differences (at a significance level of 0.05) between the reconstruction strategies at all three dose levels. There were no significant differences in observer performance for any of the dose levels.     

Fusion Forward–Backward Pursuit Algorithm for Compressed Sensing

The Forward–Backward Pursuit (FBP), which is a recently proposed method, receives wide attention due to the high reconstruction accuracy. In this paper, we use the fusion strategy and propose the Fusion Forward–Backward Pursuit (FFBP) algorithm. This strategy only needs the reconstruction information of two FBP with different parameters. According to the termination conditions of the FBP algorithm, FFBP adopts different operation strategies, during the signal reconstruction. Without other priori information, FFBP effectively improves the exact reconstruction rate, compared with the original algorithm. Moreover, FFBP, which fuses two FBP with non-optimal parameter, can reconstruct a better signal than a single FBP with optimal parameter. We demonstrate the advantage of the proposed method through numerical simulations.     

Comments on the filtered backprojection algorithm, rangeconditions, and the pseudoinverse solution

The filtered backprojection (FBP) algorithm is widely used in computed tomography for inverting the two-dimensional Radon transform. In this paper, we analyze the processing of an inconsistent data function by the FBP algorithm (in its continuous form). Specifically, we demonstrate that an image reconstructed using the FBP algorithm can be represented as the sum of a pseudoinverse solution and a residual image generated from an inconsistent component of the measured data. This reveals that, when the original data function is in the range of the Radon transform, the image reconstructed using the FBP algorithm corresponds to the pseudoinverse solution. When the data function is inconsistent, we demonstrate that the FBP algorithm makes use of a nonorthogonal projection of the data function to the range of the Radon transform.     

基于压缩感知的双向阈值匹配追踪算法

最近提出的前向后向算法(Forward-backward Pursuit,FBP)因为重构精度较高受到人们更多关注.但是FBP算法没有考虑到当前迭代残差信号的变化,每次迭代选取的原子和删减原子的数目是固定的.鉴于此,提出了双向阈值匹配追踪算法(Ovonic Threshold Matching Pursuit,OTMP).OTMP前向原子选择过程通过限制等距性质(RIP)和残差的条件选出部分新增加原子,在回溯过程中通过当前迭代的重构水平剔除可能错误的原子.实验表明,在一定条件下OTMP时间复杂度和正交匹配追踪算法(Orthogonal Matching Pursuit,OMP),子空间追踪算法(Subspace Pursuit,SP)相当,重构精度明显高于SP,FBP算法和其他几种贪婪算法.     

Quantitative comparison of FBP,EM, and Bayesian reconstruction algorithms for the IndyPET scanner

We quantitatively compare filtered backprojection (FBP), expectation-maximization (EM), and Bayesian reconstruction algorithms as applied to the IndyPET scanner--a dedicated research scanner which has been developed for small and intermediate field of view imaging applications. In contrast to previous approaches that rely on Monte Carlo simulations, a key feature of our investigation is the use of an empirical system kernel determined from scans of line source phantoms. This kernel is incorporated into the forward model of the EM and Bayesian algorithms to achieve resolution recovery. Three data sets are used, data collected on the IndyPET scanner using a bar phantom and a Hoffman three-dimensional brain phantom, and simulated data containing a hot lesion added to a uniform background. Reconstruction quality is analyzed quantitatively in terms of bias-variance measures (bar phantom) and mean square error (lesion phantom). We observe that without use of the empirical system kernel, the FBP, EM, and Bayesian algorithms give similar performance. However, with the inclusion of the empirical kernel, the iterative algorithms provide superior reconstructions compared with FBP, both in terms of visual quality and quantitative measures. Furthermore, Bayesian methods outperform EM. We conclude that significant improvements in reconstruction quality can be realized by combining accurate models of the system response with Bayesian reconstruction algorithms.     

O(N2log2N) filtered backprojectionreconstruction algorithm for tomography

We present a new fast reconstruction algorithm for parallel beam tomography. The new algorithm is an accelerated version of the standard filtered backprojection (FBP) reconstruction, and uses a hierarchical decomposition of the backprojection operation to reduce the computational cost from O(N(3)) to O(N(2)log(2 )N). We discuss the choice of the various parameters that affect the behavior of the algorithm, and present numerical studies that demonstrate the cost versus distortion tradeoff. Comparisons with Fourier reconstruction algorithms and a multilevel inversion algorithm by Brandt et al., both of which also have O(N(2)log(2)N) cost, suggest that the proposed hierarchical scheme has a superior cost versus distortion performance. It offers RMS reconstruction errors comparable to the FBP with considerable speedup. For an example with a 512x512-pixel image and 1024 views, the speedup achieved with a particular implementation is over 40 fold, with reconstructions visually indistinguishable from the FBP.     

一种改进的稀疏自适应压缩感知重构算法

为了优化贪婪匹配追踪算法的性能,文中基于稀疏自适应两阶段回溯型贪婪算法-前后追踪算法,提出了一种改进的线性变步长前后追踪算法。该算法结合稀疏自适应追踪算法的分阶段、变步长的思想,将迭代过程分为两个阶段,采用线性变步长进行迭代,大步长较少运行时间,小步长提升重构精度,从而减少了运行开销的同时,提升了算法的重构精度,通过仿真实验对其进行了验证,线性变步长前后追踪算法能够明显减少算法的运行时间,且提升了重构精度。