Rn 上的线性局部保控映射

设φ：Rn →Rn 是一个线性映射,对任意x∈Rn ,都存在与x有关的线性保控映射ψx ,使得φ（x）＝ψx（x）,则称φ是欧氏空间上的一个线性局部保控映射。线性保控映射是线性局部保控映射,其逆命题不成立。文中定义了两个与φ相关的Rn的子集Iφ和IIφ,如果任意Rn上的点都属于Iφ（或IIφ）,那么这个线性局部保控映射φ是线性保控映射。     

多孔薄壁扁管连续挤压模的研制

介绍了连续挤压模的生产工艺过程 ,模具主要结构及设计参数 ,分析了生产中存在的问题以及采取的措施 ,充分发挥了连续挤压设备的潜力 ,扩大了产品品种     

谈谈水泥土挡墙的合理计算

阐述了水泥土挡墙在工程基坑支护中的作用,并结合工程实例,对水泥土挡墙的合理计算模型进行了探讨。     

Dual–primal proximal point algorithms for extended convex programming

This paper presents a class of dual–primal proximal point algorithms (PPAs) for extended convex programming with linear constraints. By choosing appropriate proximal regularization matrices, the application of the general PPA to the equivalent variational inequality of the extended convex programming with linear constraints can result in easy proximal subproblems. In theory, the sequence generated by the general PPA may fail to converge since the proximal regularization matrix is asymmetric sometimes. So we construct descent directions derived from the solution obtained by the general PPA. Different step lengths and descent directions are chosen with the negligible additional computational load. The global convergence of the new algorithms is proved easily based on the fact that the sequences generated are Fejér monotone. Furthermore, we provide a simple proof for the O(1/t) convergence rate of these algorithms.     

一种相控阵天线安装精度检测与校准

文中论述了一种相控阵雷达天线安装后的精度检测方法。按照雷达天线安装后的几何形态,采用光学测量仪器进行相关的数据采集,建立检测的数学模型,利用线性回归法以及最小二乘法进行数据拟合,计算出安装后雷达天线底面与水平面的最大夹角和天线边缘与正北方向的夹角,并进行了试验误差评估和分析,依据检测数据对雷达天线的水平和方位角度进行校...     

Locally linear discriminant embedding: An efficient method for face recognition

In this paper an efficient feature extraction method named as locally linear discriminant embedding (LLDE) is proposed for face recognition. It is well known that a point can be linearly reconstructed by its neighbors and the reconstruction weights are under the sum-to-one constraint in the classical locally linear embedding (LLE). So the constrained weights obey an important symmetry: for any particular data point, they are invariant to rotations, rescalings and translations. The latter two are introduced to the proposed method to strengthen the classification ability of the original LLE. The data with different class labels are translated by the corresponding vectors and those belonging to the same class are translated by the same vector. In order to cluster the data with the same label closer, they are also rescaled to some extent. So after translation and rescaling, the discriminability of the data will be improved significantly. The proposed method is compared with some related feature extraction methods such as maximum margin criterion (MMC), as well as other supervised manifold learning-based approaches, for example ensemble unified LLE and linear discriminant analysis (En-ULLELDA), locally linear discriminant analysis (LLDA). Experimental results on Yale and CMU PIE face databases convince us that the proposed method provides a better representation of the class information and obtains much higher recognition accuracies.     

Radiometric normalization and image mosaic generation of ASTER thermal infrared data: An application to extensive sand sheets and dune fields

Data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) have a significant advantage over previous datasets because of the combination of high spatial resolution (15-90 m) and enhanced multispectral capabilities, particularly in the thermal infrared (TIR) atmospheric window (8-12 μm) of the Earth where common silicate minerals are more easily identified. However, the 60 km swath width of ASTER can limit the effectiveness of accurately tracing large-scale features, such as eolian sediment transport pathways, over long distances. The primary goal of this paper is to describe a method for generating a seamless and radiometrically accurate ASTER TIR mosaic of atmospherically corrected radiance and from that, extract surface emissivity for arid lands, specifically, sand seas. The Gran Desierto in northern Sonora, Mexico was used as a test location for the radiometric normalization technique because of past remote sensing studies of the region, its compositional diversity, and its size. A linear approach was taken to transform adjacent image swaths into a direct linear relationship between image acquisition dates. Pseudo-invariant features (PIFs) were selected using a threshold of correlation between radiance values, and change-pixels were excluded from the linear regression used to determine correction factors. The degree of spectral correlation between overlapping pixels is directly related to the amount of surface change over time; therefore, the gain and offsets between scenes were based only on regions of high spectral correlation. The result was a series of radiometrically normalized radiance-at-surface images that were combined with a minimum of image edge seams present. These edges were subsequently blended to create the final mosaic. The advantages of this approach for TIR radiance (as opposed to emissivity) data include the ability to: (1) analyze data acquired on different dates (with potentially very different surface temperatures) as one seamless compositional dataset; (2) perform decorrelation stretches (DCS) on the entire dataset in order to identify and discriminate compositional units; and (3) separate brightness temperature from surface emissivity for quantitative compositional analysis of the surface, reducing seam-line error in the emissivity mosaic. The approach presented here is valid for any ASTER-related study of large geographic regions where numerous images spanning different temporal and atmospheric conditions are encountered.     

基于模糊控制的无刷直流电机建模仿真新方法

为提高无刷直流电动机(BLDCM)控制系统的精度,本文根据电机的数学模型,基于Matlab仿真平台构建了BLDCM电流、转速模糊PI复合控制的双闭环控制系统的仿真模型。该模型采用了一种基于分段线性化的思想,利用Simulink中的Look-Up Table对梯形波感应电动势和电磁转矩进行快速建模的方法。仿真结果表明,该模型准确易行、控制精度高,为实际BLDCM控制系统的设计和调试提供了有效的工具。     

面向不同利益相关者的IT投资决策模型

为了响应不同利益相关者在IT投资决策过程中的不同需求,把备选项目看作一个组合,综合IT项目的战略对应和财务收益为目标,权衡其成本、收益和风险,构建基于模糊多目标规划的IT投资决策模型,其中模糊数用来刻画不确定的项目信息。通过改变各临界值和求解过程中产生的参数,模型支持各种假设分析。最后用案例说明模型的用法和功能。     

基于GH-PKC体制的盲签名方案

GH-PKC是一种新的基于GF(q)上三级线性反馈移位寄存器序列的公钥密码体制。其安全性基于有限域GF(q3)上的离散对数困难问题,但运算却在有限域GF(q)中进行。文中给出了一种新的基于GH-PKC的类ELGamal数字签名算法,并在此基础上构建了基于GH-PKC的盲签名方案,其安全性等价于解GF(q3)上离散对数困难问题,但是传输的数据量只有传统方案的1/3。