Critical area computation for real defects and arbitrary conductor shapes

In current critical area models, it is generally assumed the defect outlines are circular and the conductors to be rectangle or the merger of rectangles. However, real defects and conductors associated with optimal layout design exhibit a great variety of shapes. Based on mathematical morphology, a new critical area model is presented, which can be used to estimate the critical area of short circuit, open circuit and pinhole. Based on the new model, the efficient validity check algorithms are explored to extract critical areas of short circuit, open circuit and pinhole from layouts. The results of experiment on an approximate layout of ${4\times 4}$ shifts register show that the new model predicts the critical areas accurately. These results suggest that the proposed model and algorithm could provide new approaches for yield prediction.     

A novel sensitivity model for short nets

For modern processes at deep sub-micron technology nodes, yield design, especially the design at the layout stage is an important way to deal with the problem of manufacturability and yield. In order to reduce the yield loss caused by redundancy material defects, the choice of nets to be optimized at first is an important step in the process of layout optimization. This paper provides a new sensitivity model for a short net, which is net-based and reflects the size of the critical area between a single net and the nets around it. Since this model is based on a single net and includes the information of the surrounding nets, the critical area between the single net and surrounding nets can be reduced at the same time. In this way, the efficiency of layout optimization becomes higher. According to experimental observations, this sensitivity model can be used to choose the position for optimization. Compared with the chip-area-based and basic- layout-based sensitivity models, our sensitivity model not only has higher efficiency, but also confirms that choosing the net to be optimized at first improves the design.     

Cryptanalysis of an ergodic chaotic encryption algorithm

In this paper, we present the results for the security and the possible attacks on a new symmetric key encryption algorithm based on the ergodicity property of a logistic map. After analysis, we use mathematical induction to prove that the algorithm can be attacked by a chosen plaintext attack successfully and give an example to show how to attack it. According to the cryptanalysis of the original algorithm, we improve the original algorithm, and make a brief cryptanalysis. Compared with the original algorithm, the improved algorithm is able to resist a chosen plaintext attack and retain a considerable number of advantages of the original algorithm such as encryption speed, sensitive dependence on the key, strong anti-attack capability, and so on.     

Yield estimation of metallic layers in integrated circuits

In the existing models of estimating the yield and critical area, the defect outline is usually assumed to be circular, but the observed real defect outlines are irregular in shape. In this paper, estimation of the yield and critical area is made using the Monte Carlo technique and the relationship between the errors of yield estimated by circular defect and the rectangle degree of the defect is analysed. The rectangular model of a real defect is presented, and the yield model is provided correspondingly. The models take into account an outline similar to that of an original defect, the characteristics of two-dimensional distribution of defects, the feature of a layout routing, and the character of yield estimation. In order to make the models practicable, the critical area computations related to rectangular defect and regular (vertical or horizontal) routing are discussed. The critical areas associated with rectangular defect and non-regular routing are developed also, based on the mathematical morphology. The experimental results show that the new yield model may predict the yield caused by real defects more accurately than the circular model. It is significant that the yield is accurately estimated using the proposed model for IC metals.     

An interconnect width and spacing optimization model considering scattering effect

As the feature size of the CMOS integrated circuit continues to shrink, the more and more serious scattering effect has a serious impact on interconnection performance, such as delay and bandwidth. Based on the impact of the scattering effect on latency and bandwidth, this paper first presents the quality-factor model which optimises latency and bandwidth effectively with the consideration of the scattering effect. Then we obtain the analytical model of line width and spacing with application of curve-fitting method. The proposed model has been verified and compared based on the nano-scale CMOS technology. This optimisation model algorithm is simple and can be applied to the interconnection system optimal design of nano-scale integrated circuits.     

Extraction of temperature dependences of small-signal model parameters in SiGe HBT HICUM model

In this work, temperature dependences of small-signal model parameters in the SiGe HBT HICUM model are presented. Electrical elements in the small-signal equivalent circuit are first extracted at each temperature, then the temperature dependences are determined by the series of extracted temperature coefficients, based on the established temperature formulas for corresponding model parameters. The proposed method is validated by a 1 × 0.2 × 16 μm~2 SiGe HBT over a wide temperature range(from 218 K to 473 K), and good matching is obtained between the extracted and modeled results. Therefore, we believe that the proposed extraction flow of model parameter temperature dependence is reliable for characterizing the transistor performance and guiding the circuit design over a wide temperature range.     

USING AN EVOLUTIONARY ALGORITHM BASED ON CELL DIVISION OPERATION TO CALCULATE GROUND-STATE ENERGIES OF DOUBLE-ELECTRON SYSTEMS IN MAGNETIC FIELDS

In this paper we adopt a new approach－the evolutionary algorithm based　on cell division operation－to deal with ground-state energies of double-electron systems. This algorithm is based on the evolution of sets and can incorporate other search algorithms. Firstly, we make a search for several good subsets of solution space at the same time. Then, we make a fine search in the neighbourhood of some better points obtained in the first step to determine the final optimal results. In addition, the cell division enables the solution subspaces to become smaller and smaller, and thus increase the convergence speed. We have tested this approach on double-electron systems in magnetic fields, and the results obtained have shown that it can improve not only the efficiency but also the accuracy of the calculations compared with other methods.     

Robust speech features representation based on computational auditory model

A speech signal processing and features extracting method based on computational auditory model is proposed. The computational model is based on psychological, physiological knowledge and digital signal processing methods. In each stage of a hearing perception system, there is a corresponding computational model to simulate its function. Based on this model, speech features are extracted. In each stage, the features in different kinds of level are extracted. A further processing for primary auditory spectrum based on lateral inhibition is proposed to extract much more robust speech features. All these features can be regarded as the internal representations of speech stimulation in hearing system. The robust speech recognition experiments are conducted to test the robustness of the features. Results show that the representations based on the proposed computational auditory model are robust representations for speech signals.     

The influences of model parameters on the characteristics of memristors

As the fourth passive circuit component, a memristor is a nonlinear resistor that can "remember" the amount of charge passing through it. The characteristic of "remembering" the charge and non-volatility makes memristors great potential candidates in many fields. Nowadays, only a few groups have the ability to fabricate memristors, and most researchers study them by theoretic analysis and simulation. In this paper, we first analyse the theoretical base and characteristics of memristors, then use a simulation program with integrated circuit emphasis as our tool to simulate the theoretical model of memristors and change the parameters in the model to see the influence of each parameter on the characteristics. Our work supplies researchers engaged in memristor-based circuits with advice on how to choose the proper parameters.     

QCD chiral phase transition and critical exponents within the nonextensive Polyakov-Nambu-Jona-Lasinio model

We present a nonextensive version of the Polyakov-Nambu-Jona-Lasinio model that is based on nonextentive statistical mechanics.This new statistics model is characterized by a dimensionless nonextensivity parameter q that accounts for all possible effects violating the assumptions of the Boltzmann-Gibbs(BG) statistics(for q→ 1,it returns to the BG case).Based on the nonextensive Polyakov-Nambu-Jona-Lasinio model,we discussed the influence of nonextensive effects on the curvature of the phase diagram at μ=0 and especially on the location of the critical end point(CEP).A new and interesting phenomenon we found is that with an increase in q,the CEP position initially shifts toward the direction of larger chemical potential and lower temperature.However,when q is larger than a critical value q_c,the CEP position moves in the opposite direction.In other words,as q increases,the CEP position moves in the direction of smaller chemical potential and higher temperature.This U-turn phenomenon may be important for the search of CEP in relativistic heavy-ion collisions,in which the validity of BG statistics is questionable due to strong fluctuations and long-range correlations,and nonextensive effects begin to manifest themselves.In addition,we calculated the influence of the nonextensive effects on the critical exponents and found that they remain almost constant with q.     

X光图像中缺陷的自动提取方法研究

针对炭素制品X光图像的特点,对其缺陷的提取技术进行了研究,提出了基于迭代的阈值构造方法和基于数学形态学的边缘提取算法。为快速准确地提取缺陷,设计了目标边界提取算法和基于小波变换的图像增强算法,实现了原始图像中目标区域的增强及其背景的去除。在此基础上,为排除噪声干扰的影响,采用数学形态学和迭代阈值分割相结合的方法从目标区域中提取出缺陷区域,并在迭代阈值分割的基础上,利用基于数学形态学的边缘提取算法提取了缺陷的边缘。实验结果表明,该法很好地实现了缺陷区域及其边缘的自动提取,且受噪声影响很小,为进一步的缺陷特征参量的提取与选择奠定了良好的基础。     

基于地物光谱特征分析的高分辨率遥感图像水上桥梁提取

水上桥梁是一种典型的人造目标。利用高分辨率遥感图像进行水上桥梁提取,对于民用、军用和商业都具有重要意义。论文在分析地物光谱特征的基础上,提出了一种利用高分辨率近红外波段遥感图像进行水上桥梁提取的方法。首先,根据水体在近红外波段的光谱特征,采用迭代法选取阈值提取水体信息,以限制桥梁提取的空间范围;然后,对水体信息进行数学形态学运算,以连接因桥梁而断开的水体;其次,对数学形态学操作前后的水体信息进行叠加分析,以提取候选桥梁目标;最后,在桥梁先验特征知识的辅助下,去除伪桥梁目标。论文设计了仿真实验,以验证方法的有效性和适用性。实验结果表明,基于地物光谱特征分析的高分辨率遥感图像水上桥梁提取方法是行之有效的。     

一种基于修正扩展形态学算子的高光谱遥感图像端元提取算法

形态学算子反映了像素的空间相关性信息,将其应用于高光谱遥感图像端元提取可以有效地提升算法性能,本文针对已经普遍用于高光谱遥感图像端元提取的扩展形态学算子在像元排序规则和替换准则上存在的局限性,引入了基准向量的概念并给出计算方法,提出了修正扩展形态学算子.修正后的排序规则和替换准则避免了图像中不同类别交界处的交叉替换现象,保证了正确的覆盖方向,是提高端元提取效果的关键步骤.通过修正扩展形态学算子的基本膨胀和腐蚀运算,定义了相应的开-闭运算和闭-开运算,由此得出了端元判定向量,并给出端元提取算法的详细流程.基于扩展形态学的自动端元提取算法可以综合考虑光谱和空间信息,端元提取效果优于仅依靠光谱信息的算法.算法由IDL7.0实现,并在AVIRIS于Cupritc地区的高光谱遥感图像上进行实验,实验结果从光谱曲线相似性、端元平均相似度和相应地物分布图等方面证明了算法的有效性.     

基于图论的空间热网拓扑结构

针对多热源环状热网水力工况分析所涉及的非平面网、及故障工况供回水管网不对称的问题,基于图论提出一种建立空间热网拓扑结构的方法:根据供回水管网基本结构信息,采用面向对象的程序设计方法,定义图并包含相关算法,自动生成关联矩阵和基本回路矩阵;在平面图的基础上,结合热源和热用户信息,采用广度优先搜索生成空间热网的"树",据此构建空间热网的基本关联矩阵和基本回路矩阵.研制了建立多热源环状空间热网拓扑结构的程序,通过哈尔滨开发区热网的模拟,对程序的计算性能进行验证.该方法以图的相关算法为基础,能适应不同型式管网的计算,为复杂热网的水力工况分析和非对称热网的计算提供手段.     

基于光流的运动小目标检测算法

运动目标的检测是目标识别与跟踪的关键技术之一。光流技术是一种以物体的运动特征来检测目标的方法,它的提出为运动小目标的检测开辟了新的空间。在一个搜索跟踪系统中使用光流技术检测和跟踪空中小目标,目标大概为5～10个像素,而且背景复杂,相机抖动,普通分割算法无法得到小目标。在目标的运动明显异于背景的情况下,通过利用基于光流的目标检测算法来检测出小目标,同时运用高斯金字塔模型,提高算法的运算速度。试验结果表明提出的基于光流的检测算法在背景运动的红外图像中取得了较好的效果。     

基于扩展数学形态学的高光谱图像异常检测

提出了一种新型的基于扩展数学形态和光谱相似度测量的高光谱图像异常榆测方法.在日标与背景未知的情况下.同时利用光谱和空间信息实现日标的定位与检测,实现离光谱遥感数据的日标检测.通过扩展的膨胀和腐蚀操作实现目标特征提取;通过正交投影散度计算扩展形态学操作的累加距离确定排序关系并利用其融合特征提取结果实现特征提取结果的融合.算法性能通过合成的OMIS数据进行评价.与经典异常检测RX算法进行比较.并应用于具有相似光谱特征目标的区分.实验证明,本文提出的算法性能优于RX算法.具有低虚警率的异常目标检测结果,并且能够较好地区分了相似光谱特征的异常日标.     

基于形态学的不完全性骨折CT图像裂痕定位

针对不完全性骨折的CT图像损伤位置不易明确定位的问题,提出了一种基于数学形态学的裂痕定位算法。为了从CT图像中获得准确的骨质区域,在CIE Lab均匀色彩空间对原始图像进行双边滤波去噪,利用最大类间方差法计算出最佳阈值,从而分离出骨质区域,采用数学形态学中的黑帽运算结合Canny边缘检测算子对裂痕位置进行精确定位。实验结果表明,能够自动提取并定位不完全性骨折CT图像的裂痕区域。算法易于实现,具有较强的鲁棒性和实用性,方便了医学影像诊断。     

Hybrid neural nets with poisson and gaussian connectivities

The dynamic behavior of neural nets with different patterns of interneuronal synaptic connectivity is investigated. Our method is based on probabilistic neural nets for the net structure and dynamics. Each net is divided into several different subsystems, which are characterized by different distribution laws for the number of connections that the neurons make. We start from the binomial distribution, which, under appropriate conditions, reduces to the Poisson and Gaussian distributions. The overall net now acquires a hybrid character. The expression for the neural activity is generalized to include this effect, and new expressions are derived, based on the isolated single-net equations. The dynamics of nets with sustained external inputs is also studied. The results obtained by this approach also show multiple stability and multiple hysteresis effects, as in the case of single nets. The differences between pure Poisson, Gaussian, and hybrid nets are explained in terms of the structural properties of the model. As expected, the hybrid case falls in between the two other distributions. Finally, we performed Monte Carlo computer calculations for the hybrid nets. For the range of parameters examined we find very good agreement with the developed formalism