Assignment of inter-die signals in a simplified wiring model for die-stacking SiP designs

Compared with traditional flow in IC designs, the assignment of the inter-die signals between different dies is an important stage in a die-stacking SiP design. In this paper, given a tolerant spacing rule between two inter-die signals, the crossing constraint between two inter-die signals can be firstly defined for the bonding wires in a die-stacking SiP design with a simplified wiring model [7]. Furthermore, based on the connection constraint on any inter-die signal, the capacity constraint on any assigned pad on dies and the crossing constraint between two inter-die signals, an integer linear programming-based (ILP-based) approach is proposed to assign all the inter-die signals to minimize the total wirelength in a die-stacking SiP design. Compared with Lin’s two-stage approach [4] for some tested examples without a tolerant spacing distance between two inter-die signals in an Euclidean wiring model, the experimental results show that our proposed ILP-based approach increases 4.5% of CPU time and reduces 6.2% of total wirelength to assign all the inter-die signals on the average. Besides that, compared with Yan’s iterative approach [6] for some tested examples without a tolerant spacing distance between two inter-die signals in an Euclidean wiring model, the experimental results show that our proposed ILP-based approach uses reasonable CPU time to reduce 5.3% of total wirelength to assign all the inter-die signals on the average. Compared with Lin’s modified two-stage approach and Yan’s modified iterative approach for some dense tested examples with a tolerant spacing distance between two inter-die signals in a simplified wiring model [7], the experimental results show that Lin’s modified two-stage approach only achieves 95.9% of the assignment ratio on the average, Yan’s modified iterative approach only achieves 96.6% of the assignment ratio on the average and our proposed ILP-based approach uses reasonable CPU time to achieve 100% of the assignment ratio.     

A human visual system-driven image segmentation algorithm

This paper presents a novel image segmentation algorithm driven by human visual system (HVS) properties. Segmentation quality metrics, based on perceptual properties of HVS with respect to segmentation, are integrated into an energy function. The energy function encodes the HVS properties from both region-based and boundary-based perspectives, where the just-noticeable difference (JND) model is employed when calculating the difference between the image contents. Extensive experiments are carried out to compare the performances of three variations of the presented algorithm and several representative segmentation and clustering algorithms available in the literature. The results show superior performance of our approach.     

Wavelet-based hybrid natural image modeling using generalized Gaussian and α-stable distributions

Natural image is characterized by its highly kurtotic and heavy-tailed distribution in wavelet domain. These typical non-Gaussian statistics are commonly described by generalized Gaussian density (GGD) or α-stable distribution. However, each of the two models has its own deficiency to capture the variety and complexity of real world scenes. Considering the statistical properties of GGD and α-stable distributions respectively, in this paper we propose a hybrid statistical model of natural image’s wavelet coefficients which is better in describing the leptokurtosis and heavy tails simultaneously. Based on a clever fusion of GGD and α-stable functions, we establish the optimal parametric hybrid model, and a close-formed Kullback–Leibler divergence of the hybrid model is derived for evaluating model accuracy. Experiment results and comparative studies demonstrate that the proposed hybrid model is closer to the true distribution of natural image’s wavelet coefficients than the single modeling using GGD or α-stable, while is beneficial for applications such as image comparison.     

Graph-based video fingerprinting using double optimal projection

A double optimal projection method that involves projections for intra-cluster and inter-cluster dimensionality reduction are proposed for video fingerprinting. The video is initially set as a graph with frames as its vertices in a high-dimensional space. A similarity measure that can compute the weights of the edges is then proposed. Subsequently, the video frames are partitioned into different clusters based on the graph model. Double optimal projection is used to explore the optimal mapping points in a low-dimensional space to reduce the video dimensions. The statistics and geometrical fingerprints are generated to determine whether a query video is copied from one of the videos in the database. During matching, the video can be roughly matched by utilizing the statistics fingerprint. Further matching is thereafter performed in the corresponding group using geometrical fingerprints. Experimental results show the good performance of the proposed video fingerprinting method in robustness and discrimination.     

An analytical model for optimizing the performance of graphene based silicon Schottky barrier solar cells

In this paper, a model taking into account the effects of carrier loss mechanisms has been developed. The model simulates the photovoltaic properties of the graphene/n-type silicon Schottky barrier solar cells (G/n-Si_SBSC), and it can reproduce the experimentally determined parameters of the G/n-Si_SBSC. To overcome the low efficiencies of G/n-Si_SBSC, their performances have been optimized by modifying the work function of graphene and Si properties, accounted for variation of its thickness and doping level. The obtained results show that the work function of graphene has the major impact on the device performance. Also, the temperature dependence of the G/n-Si_SBSC performance is investigated.     

AR模型功率谱估计在抗干扰中的DSP实现

本文在AR模型(自回归模型)功率谱估计方法的基础上,对其在抗干扰领域中的应用进行了研究,提出了自适应滤除干扰信号的方案,并对该方案进行了DSP实现。实验结果表明,该方案在自适应去除多个干扰信号方面是行之有效的。     

一种多人脸跟踪算法的研究与实现

结合人脸的运动模型提出了一种多人脸的跟踪算法,通过使用跟踪稳定系数来解决多人脸跟踪过程中目标发生粘连重叠或者由于目标检测质量的原因造成跟踪目标丢失等各种问题;同时目标跟踪器提供一个预测搜索区域指导下一帧的定位,从而进一步提高定位的速度.实验结果表明此算法具有很好的准确性和实时性.     

数据挖掘技术及其在经营分析系统中的应用

为了在市场竞争中保持及发展客户、提升客户价值,运营商迫切需要了解客户的行为特征以及业务发展、收益、营销、服务等方面的运营情况,以便及时制定更加合理和高效的经营策略,更好地在竞争中掌握主动.于是,电信企业纷纷着手建立数据仓库和在线分析处理(OLAP)系统,通过对运营支撑系统多年积累的业务数据进行整合和分析,以获得有价值的分析结果.但是,OLAP侧重的是对历史数据的分析,回答的是"过去发生了什么和为什么会发生"的问题,而运营商在对过去和现在的经营状况进行分析掌握的同时,更加渴望对整个企业未来的发展状况做出比较完整、合理、准确的分析和预测,于是,数据挖掘技术由于能够发现潜在的知识以及能够回答"将要发生什么"的问题而被电信企业加以"重用".本文简要阐述了数据挖掘技术、主要模型及方法、数据挖掘的实施步骤,并结合具体的案例说明数据挖掘在电信行业经营分析系统中的应用.     

单向双端口SRAM的测试算法

描述了一种检测单向双端口 SRAM失效的算法 ,采用了基于字的测试方法 ,可以有效地检测字间失效、字内失效和同时读写失效 ,具有失效覆盖率高和测试时间复杂度低的优点。     

Si上外延的n型3C-SiC欧姆接触研究

用LPCVD在Si(111)上异质外延了n型3C-SiC,并在所外延的3C-SiC上蒸发Au/Ti,通过不同温度下的RTA(快速热退火)形成欧姆接触。用两种不同的传输线模型对Ti/3C-SiC欧姆接触的ρc(比接触电阻率)进行测量,在750°C退火后Ti/3C-SiC的ρc达到了最低值为3.68×10-5Ω·cm2,这满足了应用的要求。AES分析结果还表明由于Ti的氧化,更高温度下的退火会使ρc增大。