中等起伏目标最佳检测器的性能分析

推导出了中等起伏雷达目标最佳检测器主要性能参数的显式表达式。采用分析和模拟的方法将最佳检测器同广义特征滤波方法的性能进行了比较，结果说明这种针对部分相关目标的最佳检测方法具有更优良的检测性能。     

Outliers in multilevel data

This paper offers the data analyst a range of practical procedures for dealing with outliers in multilevel data. It first develops several techniques for data exploration for outliers and outlier analysis and then applies these to the detailed analysis of outliers in two large scale multilevel data sets from educational contexts. The techniques include the use of deviance reduction, measures based on residuals, leverage values, hierarchical cluster analysis and a measure called DFITS. Outlier analysis is more complex in a multilevel data set than in, say, a univariate sample or a set of regression data, where the concept of an outlying value is straightforward. In the multilevel situation one has to consider, for example, at what level or levels a particular response is outlying, and in respect of which explanatory variables; furthermore, the treatment of a particular response at one level may affect its status or the status of other units at other levels in the model.     

On shape detection in noisy images with particular reference to ultrasonography

We discuss the detection of a connected shape in a noisy image. Two types of image are considered: in the first a degraded outline of the shape is visible, while in the second the data are a corrupted version of the shape itself. In the first type the shape is defined by a thin outline of pixels with records that are different from those at pixels inside and outside the shape, while in the second type the shape is defined by its edge and pixels inside and outside the shape have different records. Our motivation is the identification of cross-sectional head shapes in ultrasound images of human fetuses. We describe and discuss a new approach to detecting shapes in images of the first type that uses a specially designed filter function that iteratively identifies the outline pixels of the head. We then suggest a way based on the cascade algorithm introduced by Jubb and Jennison (1991) of improving and considerably increasing the speed of a method proposed by Storvik (1994) for detecting edges in images of the second type.     

瑞利衰落信道下差分跳频同步多用户性能

在瑞利衰落信道和同步多用户环境下,分别针对逐符号检测和按序列检测两种信号检测方法,从理论上分析了差分跳频通信系统的误符号性能,同时做出相应的计算机仿真。仿真结果证实了差分跳频通信技术和按序列检测方法的结合,使系统的多用户性能得到了一定程度的提升。     

未知参数多项式相位信号的最优检测及性能

根据Neyman-Pearson(NP)准则,利用广义似然比检验方法,给出了未知参数多项式相位信号的最优检测器。在相位多项式次数分别为1或2时,周期图、chirp傅里叶变换检测即为对应的最优检测器。推导了检验统计量的概率密度函数以及虚警概率和检测概率,揭示了多项式相位信号检测中信号能量噪声比、信号参数空间中搜索点数、虚警概率和检测概率之间的关系。仿真结果验证了理论分析的有效性。     

非线性HVS边界提取算子

为对人眼视觉系统(human visual system以下简称HVS)的明暗分界感觉进行较准确的计算机模拟,根据HVS对光强度信号的非线性响应特征,作者对司明状态下的HVS边界感觉机制进行了细致研究,提出新的非线性算子,把该算子用于图像边界提取的计算机模拟,经试验验证,与人眼感觉符合较好.     

指数函数分解法的CPM非相干序列估计

连续相位调制本身所具有的高效频谱和功率利用率使得这种调制方式非常适合应用于无线通信环境中,但其解调的复杂度也随着记忆长度和进制数的增加呈指数增长。该文给出的非相干序列估计算法,通过将大量的参考信号分解成矢量形式,将信号间的相关运算转化为矢量乘法运算,可以有效地降低CPM解调器前端复杂度;在序列译码阶段,采用的是指数窗的截短方法,在不损失性能的前提下有效降低了解调器后端的复杂度。     

应用贪心算法的次最优MC-CDMA检测机(英文)

应用贪心算法提出了一种次最优ＭＣ－ＣＤＭＡ检测机。仿真结果表明，与传统检测机比较，它据有次最优的性能，但结构比最优检测机简单。     

Tracking Edges, Corners and Vertices in an Image

Abstract.  In a range of imaging problems, particularly those where the images are of man-made objects, edges join at points which comprise three or more distinct boundaries between textures. In such cases the set of edges in the plane forms what a mathematician would call a planar graph. Smooth edges in the graph meet one another at junctions, called 'vertices', the 'degrees' of which denote the respective numbers of edges that join there. Conventional image reconstruction methods do not always draw clear distinctions among different degrees of junction, however. In such cases the algorithm is, in a sense, too locally adaptive; it inserts junctions without checking more globally to determine whether another configuration might be more suitable. In this paper we suggest an alternative approach to edge reconstruction, which combines a junction classification step with an edge-tracking routine. The algorithm still makes its decisions locally, so that the method retains an adaptive character. However, the fact that it focuses specifically on estimating the degree of a junction means that it is relatively unlikely to insert multiple low-degree junctions when evidence in the data supports the existence of a single high-degree junction. Numerical and theoretical properties of the method are explored, and theoretical optimality is discussed. The technique is based on local least-squares, or local likelihood in the case of Gaussian data. This feature, and the fact that the algorithm takes a tracking approach which does not require analysis of the full spatial data set, mean that it is relatively simple to implement.     

应用神经网络粒子群算法的多用户检测

为了减少最优多有户检测器的计算复杂度,提出了一种融合粒子群优化算法和神经网络的神经网络粒子群优化算法,并设计了一种解决CDMA通信系统的多用户检测问题的新方法。该方法是把神经网络嵌入到粒子群优化算法的每一代中以改进算法性能。通过混合神经网络到PSO中,还可以加快PSO的收敛速度,减少计算复杂度。仿真结果证明了所设计的检测器无论抗多址干扰能力和抗远近效应能力都优于应用Hopfield神经网络、遗传算法和粒子群算法的多用户检测器。