脑电逆问题的一种分域迭代聚焦算法

脑电逆问题是一个欠定问题,引入适当的约束或迭代技巧是改善解的性能的有效途径．该文提出了一种将自相干增强算法(SCEA)和迭代聚焦算法(FOCUSS)相结合的新算法．该方法以最小模解为出发点,对其用聚类算法进行分区和自相干增强,然后进行遮代聚焦．针对皮层源的仿真计算表明,该方法可实现对不同强度的多源成像．     

LFMCW雷达信号多周期模糊函数分析

给出了LFMCW雷达信号的多周期模糊函数,并与单周期信号进行了比较。讨论了在单周期和多周期的模糊函数联系,沿主轴切割模糊函数的性质和体积有限方面上两者特征的差别。仿真结果表明,增大周期可提高多普勒分辩力,但不能改善时延分辩力。     

决定飞行器隐身性能的几项原则

隐身飞机在未来的战争中有重要的战略作用。本文从隐身飞机的作战任务、本世纪90年代的美国飞机,以及低雷达截面在飞机作战中的作用几方面分析,导出决定飞行器应具有的隐身性能的几项原则,并给出计算公式和设计曲线以供参考。     

用AUTES实现雷达辐射源识别专家系统

描述了一种用自行研制的专家系统开发工具AUTES进行雷达辐射源识别专家系统开发的方法,对其中专家知识及知识库、置信度融合方法、解释器等作了详细介绍。测试和实际运用表明,该专家系统能对雷达辐射源进行高效率识别,对参数不全或参数发生一定程度畸变的雷达辐射源的识别率可达到80％以上。     

SAR图像的边沿检测方法研究

针对合成孔径雷达（SAR）图像的特点,利用小波变换的高频分量能反映边沿细节的特性,提出了一种结合小波变换、中值滤波、自适应门限判决和微分梯度算子的边沿检测方法。实验结果表明,该方法具有良好的边沿检测效果和稳定性。     

电子海图系统雷达信息转换技术的研究

提出了一种基于三角函数变换的比例乘法器法,解决了方位角和径向距离的坐标变换,最终转换为视频存储器中的位图地址,实现了电子海图系统雷达信息的转换。     

极化SAR图像的多纹理最大似然估计

提出了一种新的极化SAR图像相干斑抑制的方法。该方法在多纹理乘性相干斑噪声模型的假设下,采用最大似然估计法来同时估计多个极化通道的纹理参数。该方法保存了极化信息,消除了极化通道间的耦合,取得较好的相干斑抑制效果;并与极化白化滤波法(PWF)作了比较。     

Non-conjugate prior distribution assessment for multivariate normal sampling

Elicitation methods are proposed for quantifying expert opinion about a multivariate normal sampling model. The natural conjugate prior family imposes a relationship between the mean vector and the covariance matrix that can portray an expert's opinion poorly. Instead we assume that opinions about the mean and the covariance are independent and suggest innovative forms of question which enable the expert to quantify separately his or her opinion about each of these parameters. Prior opinion about the mean vector is modelled by a multivariate normal distribution and about the covariance matrix by both an inverse Wishart distribution and a generalized inverse-Wishart (GIW) distribution. To construct the latter, results are developed that give insight into the GIW parameters and their interrelationships. Certain of the elicitation methods exploit unconditional assessments as fully as possible, since these can reflect an expert's beliefs more accurately than conditional assessments. Methods are illustrated through an example.     

Estimating the structural dimension of regressions via parametric inverse regression

A new estimation method for the dimension of a regression at the outset of an analysis is proposed. A linear subspace spanned by projections of the regressor vector X , which contains part or all of the modelling information for the regression of a vector Y on X , and its dimension are estimated via the means of parametric inverse regression. Smooth parametric curves are fitted to the p inverse regressions via a multivariate linear model. No restrictions are placed on the distribution of the regressors. The estimate of the dimension of the regression is based on optimal estimation procedures. A simulation study shows the method to be more powerful than sliced inverse regression in some situations.     

A penalized likelihood approach to image warping

A warping is a function that deforms images by mapping between image domains. The choice of function is formulated statistically as maximum penalized likelihood, where the likelihood measures the similarity between images after warping and the penalty is a measure of distortion of a warping. The paper addresses two issues simultaneously, of how to choose the warping function and how to assess the alignment. A new, Fourier–von Mises image model is identified, with phase differences between Fourier-transformed images having von Mises distributions. Also, new, null set distortion criteria are proposed, with each criterion uniquely minimized by a particular set of polynomial functions. A conjugate gradient algorithm is used to estimate the warping function, which is numerically approximated by a piecewise bilinear function. The method is motivated by, and used to solve, three applied problems: to register a remotely sensed image with a map, to align microscope images obtained by using different optics and to discriminate between species of fish from photographic images.