一种基于空间到达角的卫星电子侦察信号分选方法

在建立简化的卫星电子侦察空间模型的基础上，提出了一种利用空间到达角分选卫星电子侦察信号的新方法。通过仿真实验验证了这种方法的可行性。该方法可用于密集信号的预处理。     

相干源二维波达方向估计

本文分析了平面阵接收信号的协方差矩阵，发现它可分解为一个广义对称矩阵与一个非广义对称矩阵之和，利用信号协方差矩阵的这一结构特征，重点研究了相干源二维波达方向（DOA）估计．该方法通过构造一个差矩阵，求出其本特征值对应的任一特征向量，利用谱函数估计相干源二维DOA．简要分析了二维DOA估计的分维处理。     

Driver detection and recognition of lineside signals and signs at different approach speeds

A study was carried out using simulation to investigate driver responses to lineside signals and signs at various approach speeds. The objectives of the study were: (1) to find out whether train speed would significantly affect signal/sign reading; (2) to examine at which point certain types of signs or signals could be detected or recognised, and (3) to determine a speed cut-off level above which certain types of signs or signals are no longer recognisable or detectable. Fifty-seven train drivers from 12 Train Operating Companies in the UK participated in the trials. Twenty different types of lineside signs and ten types of signals were tested under six different approach speeds ranging from 100 to 350 km/h (62–218 mph). Driver performance measures were ‘time remaining to the signal/sign’ at the point of detection or recognition, and reading error rate. The results showed a significant influence of train speed on driver responses to lineside signals/signs and demonstrated a non-linear relationship between driver responses to signals/signs and approach speed. This has been used to estimate a maximum approach speed limit within which a specific signal or sign can be correctly detected or recognised. The findings and implications of the study are discussed in the paper.     

最佳基数排序

基数排序由于其效率高而被广泛应用。通常,基数排序所用的基数是10,然而,如果求得一个基数r_(best),并且用r_(best)为基数进行基数排序使排序时间达到最小,则这将具有非常重要的意义。本文给出了求r_(best)的方法,分析了以r_(best)为基数进行基数排序的时间复杂度,提出了进一步提高效率的措施,并将以r_(best)为基数的基数排序速度与以10为基数的基数排序进行了比较。     

管理信息系统建设中数据库的系统设计与管理

提出用系统的观念分类和管理数据库，挖掘数据库在管理信息系统建设中的潜在能力。     

Measurement accuracy enhancements for wideband modulated signals

Time‐domain waveform measurements of wideband modulated signals, although attractive for communication systems modeling applications, have until now lacked the required accuracy for quantitative analysis. New developments described here enhance the accuracy of these measurements, enabling their application to communication system characterization and modeling. © 2003 Wiley Periodicals, Inc. Int J RF and Microwave CAE 13: 32–39, 2003.     

Networks for sorting multitonic sequences

Lee and Batcher have designed networks that efficiently merge k separately provided sorted sequences of known lengths totalling n. We show that the design is still possible, and in fact easier to describe, if we do not make use of the lengths, or even the directions of monotonicity, of the individual sequences—the sequences can be provided in a single undelimited concatenation of length n. The depth of the simplest resulting network to sort sequences that are “k-tonic” and of length n is , generalizing Batcher's 1968 results for the extreme values of k (k=2 corresponding to merging, and k=n/2 corresponding to general sorting).The exposition is self-contained and can serve even as an introduction to sorting networks and Batcher's results.     

基于Shannon熵的飞机交流发电机振动分析

飞机交流发电机是飞机关键部件之一,监测其健康状况具有重要意义。通过设计实验数据获取平台采集交流发电机在转速上升(从6000转/分到8500转/分)、平稳运行(7500转/分)及转速下降(8500转/分到6000转/分)三个阶段的振动信号,利用符号序列Shannon熵的计算方法以及符号化方法设定合适参数对振动信号进行了处理,得出了交流发电机在三个阶段的振动信号的Shannon熵;通过初步的分析表明,交流发电机在正常状态下三个阶段的Shannon熵都比较有规律的在一定范围内变化,一旦发生振动异常将会引起Shannon熵突变;经过分析讨论,Shannon熵的突变与否是可以用来反映交流发电机在机械方面是否存在故障隐患的。     

Handling multiple objectives with biogeography-based optimization

Biogeography-based optimization (BBO) is a new evolutionary optimization method inspired by biogeography. In this paper, BBO is extended to a multi-objective optimization, and a biogeography-based multi-objective optimization (BBMO) is introduced, which uses the cluster attribute of islands to naturally decompose the problem. The proposed algorithm makes use of nondominated sorting approach to improve the convergence ability effciently. It also combines the crowding distance to guarantee the diversity of Pareto optimal solutions. We compare the BBMO with two representative state-of-the-art evolutionary multi-objective optimization methods, non-dominated sorting genetic algorithm-II (NSGA-II) and archive-based micro genetic algorithm (AMGA) in terms of three metrics. Simulation results indicate that in most cases, the proposed BBMO is able to find much better spread of solutions and converge faster to true Pareto optimal fronts than NSGA-II and AMGA do.     

Classification of cardiac sound signals using constrained tunable-Q wavelet transform

The features extracted from the cardiac sound signals are commonly used for detection and identification of heart valve disorders. In this paper, we present a new method for classification of cardiac sound signals using constrained tunable-Q wavelet transform (TQWT). The proposed method begins with a constrained TQWT based segmentation of cardiac sound signals into heart beat cycles. The features obtained from heart beat cycles of separately reconstructed heart sounds and murmur can better represent the various types of cardiac sound signals than that from containing both. Therefore, heart sounds and murmur have been separated using constrained TQWT. Then the proposed novel raw feature set has been created by the parameters that have been optimized while constraining the output of TQWT together with that of extracted by using time-domain representation and Fourier–Bessel (FB) expansion of separated heart sounds and murmur. However, the adaptively selected features have been used to obtain the final feature set for subsequent classification of cardiac sound signals using least squares support vector machine (LS-SVM) with various kernel functions. The performance of the proposed method has been validated with publicly available datasets and the results have been compared with the existing short-time Fourier transform (STFT) based method. The proposed method shows higher percentage classification accuracy of 94.01 as compared to 93.53 of STFT based method. In comparison with STFT based method, it is noteworthy that the proposed method uses well defined and lower dimensionality of feature vector that can reduce the computational complexity.