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The basic theory of the algorithm for test pattern generation using satisfiability is explored, including represent method of SAT-ATPG, search algorithm and analyses of achievement techniques. We describe how to represent circuits and fault detection problem as Conjunctive Normal Form . We improve an effient search algorithm suited to ATPG based on basic satisfiability algorithm.

本文研究了组合逻辑电路测试向量自动生成的可满足性方法,主要进行了可满足性的测试生成原理、实现算法、性能提高和测试向量的最大压缩等方面的研究,改进了一种有效的测试生成搜索算法SAT-ATPG,提出了隐含多路敏化的故障效应单路定向传播方法SOPCA、控制输入跟踪算法CIT和测试衍生算法TD,取得了较显著的效果。

The method involves an iterative procedure, which incrementally flattens a 3D triangular mesh by region growing and obtains a parameterization with free boundary. The result is then converted to a parameterization with regular boundary by conformal mapping. Our method accounts for both the angle and area distortion during parameterization, it yields a parameterization with less global distortion and no triangular flipping.

采用区域增长算法逐层展平空间三角网格,得到空间三角网格曲面的自由边界的参数化结果,并利用保形变换将自由边界的参数化结果变换为规则边界的参数化结果;同时兼顾了参数化的角度变形和面积变形,使得参数化结果具有整体变形较小的特点,并能够避免三角形折叠的现象。

For overlapping domain decomposition method, we prove the geometric convergence for continuous algorithm in the sense of energy norm by means of projection theory, analyze the convergence rate of the algorithm in detail. And we also discuss the discretization of the algorithm and its finite element implementation. Some numerical experiments are also given.

对重 叠型区域分解算法,利用投影理论,证明了连续型算法在能量模意义下的几何收敛性,详细地分析了算法的收敛速度,也讨论了算法的离散化及有限元处理,并给出了相应的数值实验。

Aiming at these problems, an expectation maximum based MAP algorithm is proposed and the performance is analyzed. The proposed algorithm avoids large matrix operations by using the EM algorithm to decompose the MIMO channel estimation problem into a series of single input single output problems. Besides, a joint estimation is carried out over multiple OFDM symbols in order to enhance the data transmission efficiency and the estimative performance of the proposed algorithm.

该算法利用EM算法把多输入输出信道估计问题化简为一系列独立的单输入输出问题,避免了大规模矩阵运算,降低了MAP算法的计算复杂度;为进一步改善MAP算法的数据传输效率及其估计性能,可通过对多个连续的OFDM符号进行联合信道估计。

In preprocessing part, it is contained normalization, segmentation, binarization, denoising, thinning and so on. And characteristic matching algorithm is used a mathematical model which is irrespective with circumrotation and displacement.

其中预处理部分由归一化、分割、二值化、去噪、细化等算法组成,且在特征匹配算法中使用了对图像旋转和平移无关的数学模型。

This paper presents the methods based on the AR model of adaptive algorithm and multi-variable AAR model algorithm to extract feature information which is related with ERD/ERS in EEG.

将脑电信号中事件去同步化/相同步化现象作为特征信息,深入讨论基于AR模型的自适应算法和多变量参数AAR模型算法在脑电信号特征提取中的应用。

A new system design based on the conception of SOC is also given. Processing and tracking algorithms. Put forward some IR image algorithms by analyzing the characteristics of IR image such as: low contrast、ununiformity、wide gray dynamic range.

在红外图像处理算法方面,分析了焦平面红外图像具有的低信噪比、宽图像动态范围及图像非均匀性等特性,结合实际硬件条件,提出了直方图归一化、去冗余灰度均衡、受限空域锐化、多帧平均等处理算法,在实际应用中取得良好效果。

The wing-edge and wing-patch data structure and fast searching method which combines the index rectangle with compass based normal vector are designed to speed the triangulation algorithm. Application in visualization of oil geological data and griding of mechanical part, the algorithm is efficient, steady and broad-spectrum. It can provide Delaunay triangular mesh for scientific computing and engineering analysis.

算法中采用了翼边、翼面型数据结构和自行设计的索引矩形与基于法矢的指南针法相结合的快速查询法,在石油地质勘探数据场可视化和机械零件网格剖分中的应用表明本文三角化算法具有高效、稳定、适用范围广的特点,能够为科学计算和工程分析提供边界一致的Delaunay三角网格。

In this algorithm, first, the time series is segmented and symbolized with the linear segment representation and the vector shape clustering method,so that each symbol can represent aprimitive and independent pattenr.Thenthe minimal occurrence representaion of time series and the association rule discovery algorithm proposed by Agrawal is combined to extrac frequent patterns of various structures from non-synchonous multiple time series.

该算法首先利用线性化分段表示法和矢量形态聚类实现时间序列的特征分割与符号化转换,然后通过将Agrawal关联模式发现算法的核心思想与时间序列最短实现表示方法相结合,实现了非同步多时间序列中多种结构频繁模式的发掘。

The energy which drives the evolution of a curve is constructed based on local image information,the alignment term enhances the speed of curve evolution,and the improved data fitting term which is based on the competition between of the shifted Heaviside functions,makes the curve converge to a better global stationary minimum.

该算法基于图像局部化信息创建驱动曲线演化的能量,引入的配准项提高了曲线的演化速度,基于曲线演化竞争的数据拟合项,使得曲线能更稳定地收敛到一个全局静态最小值,且算法对水平集函数初始化位置不敏感。

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