基于多项式变换的参数估计方法

本文给出一种采用DPT估计SNCK信号时宽—带宽积的方法,并通过仿真该估计方法的性能与其它估计方法进行比较.首先给出SNCK信号参数估计的一般过程.为了便于计算和理论推导,根据估计出的中心频率将接收到的SNCK信号搬移到零频,从而进一步估计其它参数,如采用DPT估计SNCK信号时宽带宽积.本文将重点研究采用DPT算法估计SNCK信号值的方法.     

指数势函数方法研究

长期以来 ,波峰宽度的取值问题一直是模式识别领域中势函数法的难题 .该文将模式识别问题与信号分析理论结合起来研究 ,得到了使用双边指数脉冲函数作为插值函数时的波峰宽度的解 ,给出了寻找势函数波峰宽度取值的有效方法 .在基于UCI数据的判决精度实验中 ,该文的工作得到了有效的验证 .     

基于波形匹配的星载AIS信号检测

在星载船舶信号检测的研究中,针对星载AIS系统存在时延和较大多普勒频移问题,提出了基于波形匹配的AIS信号时延频偏联合估计及其译码算法.利用AIS信号序列中的先验信息构造样本信号,通过计算并比较样本信号在不同时延和频偏下与接收信号的相关系数,估计出AIS信号的时延和频偏值,进而估计出AIS信号的码元序列.方法不需要对信号进行解调,简单易于实现.仿真结果表明,上述算法比二比特差分解调具有更好的性能,在相同信噪比下优于二比特差分解调3 dB左右,适用于存在时延和较大多普勒频偏的情况,为星载船舶信号的准确检测提供了有效方法.     

一种多径平坦衰落信道下的盲信噪比估计方法

提出一种多径平坦衰落信道下的盲信噪比估计方法.该算法首先利用数字通信信号的循环平稳统计特性构造接收信号的循环自相关矩阵,然后对该矩阵进行奇异值分解,由分解出的特征值信号子空间和噪声子空间,最后通过利用AIC信息准则分别估计信号子空间和噪声子空间的维数并最终估计出信道的平均信噪比.以MPSK信号为例进行了计算机仿真,结果表明了算法的有效性.     

基于统计方法的混沌Duffing振子弱信号检测与估计

本文研究了混沌Duffing振子在弱信号检测系统中表现出的统计特性,说明了Lyapunov指数的统计特性与弱信号检测和估计之间的关系.之前的一些研究表明,混沌系统可以用于弱信号的检测,并将Lyapunov指数作为判定混沌状态的确定性依据.但本文的研究工作表明,弱信号检测系统中的Lyapunov指数存在一定的统计特性,将其作为信号检测判据需要考虑更多因素.因此,本文从理论上分析了混沌弱信号检测系统的Lyapunov指数存在的统计特性,并利用仿真数据建立了统计模型,确立了混沌检测系统的虚警概率和检测概率的计算方法.进而推导出了策动力阈值门限的选取公式和弱信号检测信噪比,给出了信号幅度估计的方法.实验结果表明,混沌弱信号的检测和估计性能与采样时间和采样间隔密切相关,可以采用统计信号检测的理论来衡量其性能.     

基于声源时延估计的欠定盲分离方法

提出一种基于声源时延估计的二元时频掩蔽方法.通过三个接收信号实现多于多个语音源信号的欠定盲分离.利用语音信号的W-分离正交性,在时频域估计各个源信号到达接收阵列的相对时延序列;进而基于信号时延序列的估计,采用最大似然算法将时频域划分为与源信号个数相同的互不重叠的时频点集合,每个集合(近似)只包含一个源信号的所有时频分量;再通过二元时频掩蔽依次恢复出各集合所对应的源信号.该方法性能通过主观试听得到了验证,其分段信噪比增益至少为13 dB.较之欠定解混迭估计技术DUET,本文方法得到的分离信号与实际声源信号的相异度降低约3 dB.     

基于四传感器方阵的地震动目标方位角估计

针对地震动目标定位中的信号传播速度不确定性问题,提出了基于到达时间差的四传感器方阵目标方位角估计方法.从理论上推导出四传感器方阵下的目标方位角估计带边界及其最大带宽值,证明了信号传播速度与目标方位角估计之间的弱相关性.根据仿真计算深入探讨了信号传播速度和时延测量误差对目标方位角估计精度的影响.外场实验结果证明：这一方法的地震动目标方位角平均估计误差小于采用三轴地震动传感器的方法,具有一定的实用价值.     

一种DSCDMA扩频序列的盲估计方法*

针对低信噪比条件下直接序列扩频码分多址(DS-CDMA)信号扩频序列盲估计的难题,提出了一个能对同步和异步的短码调制DS-CDMA信号的扩频序列进行盲估计的新方法。该方法在分析接收信号特征结构及其相关矩阵结构的基础上,首先估计出接收信号中一个用户信号的功率、特征扩频序列的失步点及序列本身,再用已经估计出来的特征信息对相关矩阵进行缩减,以消除该用户对剩余用户信号估计的影响。依此方法,逐次迭代,最后完成对接收信号中所有用户信息的盲估计。所估计出用户信息的顺序与其功率大小密切相关,功率越大的用户,就越先被估计出     

插值FFT和滑动DTFT的科氏流量计信号处理方法

科氏流量计通过计算一次仪表输出的两路同频正弦信号的时间差来测量质量流量.实时精确估计两路信号的频率和相位差是科氏流量计数字信号处理的关键.针对科氏流量计实测信号,提出一种基于插值FFT和滑动DTFT的信号处理方法.利用插值FFT估计信号频率,通过计及负频率的改进滑动DTFT估计相位差,进而计算出时间差.方法兼顾了参数的估计精度和算法的计算效率,对比实验表明了该方法的有效性和优越性.     

基于频差修正的余弦信号频率估计算法

针对余弦振动信号的频率高精度估计需求,提出了一种基于频差修正的频率估计算法.对连续时间信号进行采样后,使用Candan算法估计出频差,运用频差对信号的频率进行修正.对修正后的信号使用Liang算法再次进行频偏估计.最后将2次估计得到的频率值相加求得最终估计频率.通过频差修正,避免了Candan算法因插值方向错误和Liang算法自身特点导致估计精度降低的问题,虽然增加了计算量,但并不影响信号实时处理.仿真结果表明:在相对频偏为任意值的情况下,改进算法的频率估计均方误差接近克拉美罗下限(CRLB),性能优于现有频率估计算法.     

Visual evoked potentials as indicators of the workload at visual display terminals

No physiological correlates are known for visual fatigue produced by prolonged viewing of visual display terminals (VDTs). The primary aim of the present study was to find a physiological correlate of a performance measure which is related to fatigue. The assumption was that a change in the state of fatigue expresses itself in fluctuations of accommodation. If indeed variations in accommodation are indicative of fatigue, then visual evoked potentials (VEPs) might be used for the objective estimation of fatigue, because pattern EPs are highly sensitive to the quality of the retinal image.

In a realistic visual task, the VEP to pattern onset and the performance to a binary task are recorded simultaneously. Both indicators of fatigue, the amplitude of the VEP and the reaction time, proved to be sensitive to the workload of the task. If accommodation effort was increased, then reaction time increased and VEP amplitude decreased. Thus, VEPs are an indicator of the workload of a visual task. This allows comparison of the fatiguing effects of various office settings on the basis of the pattern EP of a particular subject. However, because VEP amplitude and reaction time do not have the same relation amongst subjects, the pattern EP cannot be used for inter-individual comparison.     

核聚变实验中相似波形智能检索方法研究综述

随着核聚变实验数据量的与日俱增,需要针对相似波形开发智能检索方法来加速数据识别和分析。波形的相似性查询包括全序列相似查询和子序列相似查询2个方面。日本的LABCOM小组和欧盟的JET-EFDA小组在这方面做了大量的研究工作,并取得一系列成果。通过详细评述波形相似性查询方法的基本思想和关键技术,对这些方法进行分析和比较,总结了这些方法的优点和不足,并对进一步的研究方向作出了展望。      

Utilization of Discretization method on the diagnosis of optic nerve disease

The optic nerve disease is an important disease that appears commonly in public. In this paper, we propose a hybrid diagnostic system based on discretization (quantization) method and classification algorithms including C4.5 decision tree classifier, artificial neural network (ANN), and least square support vector machine (LSSVM) to diagnose the optic nerve disease from Visual Evoked Potential (VEP) signals with discrete values. The aim of this paper is to investigate the effect of Discretization method on the classification of optic nerve disease. Since the VEP signals are non-linearly-separable, low classification accuracy can be obtained by classifier algorithms. In order to overcome this problem, we have used the Discretization method as data pre-processing. The proposed method consists of two phases: (i) quantization of VEP signals using Discretization method, and (ii) diagnosis of discretized VEP signals using classification algorithms including C4.5 decision tree classifier, ANN, and LSSVM. The classification accuracies obtained by these hybrid methods (combination of C4.5 decision tree classifier-quantization method, combination of ANN-quantization method, and combination of LSSVM-quantization method) with and without quantization strategy are 84.6-96.92%, 94.20-96.76%, and 73.44-100%, respectively. As can be seen from these results, the best model used to classify the optic nerve disease from VEP signals is obtained for the combination of LSSVM classifier and quantization strategy. The obtained results denote that the proposed method can make an effective interpretation and point out the ability of design of a new intelligent assistance diagnosis system.     

Eye-strain and changes in accommodation of the eye and in visual evoked potential following quantified visual load

The measurements were made of the muscular contractions and relaxations of accommodation (infrared optometer) and of visual evoked potential (VEP) (photic stimulation) before and after one hour's visual load, checking calculations (1800 questions/hour and 900 questions/hour). The results showed that the relaxation time in accommodation lengthened and the latency of the positive wave appearing at about 100 ms in VEP increased with the increase in visual load. In addition, the complaint rate for eye-strain was higher in the group given heavier visual work. In this group, there was no significant difference in amplitude of VEP before and after the visual task. The difference in the relaxation time before and after the visual task tended to be negatively correlated to the difference in amplitude of VEP and positively related to that in the latency. In the group given lighter visual work there were significant differences in the latency and the amplitude of VEP before and after the visual task, neither were correlated to the difference in the relaxation time. These results suggest that not only peripheral hypofunction but also the decrease of centrencephalic activity level may be responsible for the development of eye-strain caused by visual tasks.     

Suppression of sidelobes in MIMO radar with distinctive piecewise non-linear frequency modulation sub-carrier

ABSTRACT

High sidelobes exist in normal multiple-input multiple-output (MIMO) radar waveforms, which utilize linear frequency modulation (LFM) or non-linear frequency modulation (NLFM) waveforms with the same subcarrier durations. Since the waveforms have the same expression, and each segment of the subcarriers can be only controlled by a few parameters to make them distinctive. This will cause comparatively high auto-correlation sidelobes in each zone of subcarriers. In order to suppress the sidelobes, new piecewise NLFM waveforms have been proposed in this paper. These novel MIMO radar waveforms are composed of three different kinds of subcarriers with totally different mathematical expressions. This is verified by the fact that the cross-correlation sidelobes between different subcarriers are much lower than the auto-correlation of each subcarrier. In addition, the number of MIMO radar waveforms has been improved significantly. As different subcarriers have their own controllable parameters, a genetic algorithm will be applied to generate the novel MIMO radar waveforms. Numerical results demonstrate the effectiveness that the auto-correlation sidelobes and the cross-correlation sidelobes of our proposed waveforms are reduced.     

BOC调制信号的抗干扰性能研究

BOC调制技术在扩频通信中的应用已日趋广泛.为此,本文在对BOC调制信号的功率谱和自相关特性进行深入研究,以及将其与BPSK调制相比存在的优势进行深入分析的基础上,以BOC(10,5),BPSK(10.23)为例,进行了基于FFT的同步捕获环路的设计与仿真,并重点就不同干信比条件下两者的捕获性能进行了分析.结果表明,在一定条件下BOC调制信号具有更好的抗干扰能力,为进一步抗干扰技术的研究提供了理论基础.     

Recent studies on multiplex driving of BTN‐LCDs

The main parameters of driving waveforms for BTN‐LCDs were investigated, and the effects on the display operation and dependence on temperature were measured. Based on experimental results, we have determined the most useful driving waveforms for practical operation, and also proposed a new driving method.     

小型化高频天线阵列的波形设计研究

主要研究了小型化表面波雷达阵列发射天线的波形特性。建立发射信号模型和波形优化目标函数，采用模拟退火算法优化求解目标函数。针对优化的跳频码序列进行仿真实验，得到仿真结果。对不同波形的自相关函数和模糊函数特性进行了研究和比较。仿真结果表明：所设计的波形较其他波形具有较优的自相关特性。研究结果可为小型化高频地波雷达的波形设计提供一种可行的方法和思路。     

Biometrics from brain electrical activity: a machine learning approach

The potential of brain electrical activity generated as a response to a visual stimulus is examined in the context of the identification of individuals. Specifically, a framework for the visual evoked potential (VEP)-based biometrics is established, whereby energy features of the gamma band within VEP signals were of particular interest. A rigorous analysis is conducted which unifies and extends results from our previous studies, in particular, with respect to 1) increased bandwidth, 2) spatial averaging, 3) more robust power spectrum features, and 4) improved classification accuracy. Simulation results on a large group of subject support the analysis     

Broadband noise suppression and feature identification of ECG waveforms using mathematical morphology and embedding theorem

The paper presents an adaptive morphological filter developed using multiscale mathematical morphology (MM) to reject broadband noise from ECG signals without affecting the feature waveforms. As a pre-processing procedure, the adaptive morphological filter cleans an ECG signal to prepare it for further analysis. The noiseless ECG signal is embedded within a two-dimensional phase space to form a binary image and the identification of the feature waveforms is carried out based on the information presented by the image. The classification of the feature waveforms is implemented by an adaptive clustering technique according to the geometric information represented by the image in the phase space. Simulation studies on ECG records from the MIT-BIH and BIDMC databases have demonstrated the effectiveness and accuracy of the proposed methods.