基于希尔伯特-黄变换的多项式相位信号检测

本文运用适合非线性非平稳信号分析的希尔伯特-黄变换,通过对含噪多项式相位信号进行经验模式分解和Hilbert谱分析,采用曲线拟合和最小二乘迭代方法,准确地估计出单一幅度恒定的多项式相位信号,从而提出了一个适合非线性非平稳信号的检测方法.仿真结果表明该方法在信噪比>10dB情况下能够准确有效地检测出非平稳信号,与基于Wigner-Ville分布的信号检测方法相比,具有更好的准确性和有效性.     

基于重叠变换和时频分析的自适应抗干扰算法

将时频分析和重叠变换结合,提出了一种新的直接序列扩频通信窄带干扰抑制算法,通过重叠变换将多分量信号分解成为一系列单分量信号并通过维格纳分布法确定单分量干扰的频率。在此基础上设计了一自适应滤波器抑制掉干扰。这种方法对平稳信号和非平衡信号同样适用。给出相应的计算机仿真结果,并与其它变换域算法进行了比较。     

Wigner-Ville分布在电力系统低频振荡中的应用

研究了基于Wigner-Ville分布（WVD）对电力系统低频振荡信号进行检测和时频分析的新方法,Wigner-Ville（wVD）分布是一种优良的时频分析方法,能够在时域频域上对非平稳信号进行联合时频分析。利用WVD的时间边缘特性和频率边缘特性,能精确地估计各模式信号的幅值、频率与主导时间;精确地分析非平稳信号的局域动态行为和特性。更好地反映振荡过程中所包含的多个模式随时间的变化规律以及模式间的相互影响,还可提高识别能力和处理效果。通过多个试验验证了该方法的有效性。     

非平稳信号分析的广义解析模态分解方法

现有的非平稳信号分析方法都有各自不同的缺陷,短时傅里叶变换的时频分辨率受不确定性原理的限制,希尔伯特黄变换存在端点效应和模态混叠,易导致模糊的时频分布;解析模态分解只适合分析频率恒定的多分量信号;针对包含多个时变模态、特别是频谱重叠的非平稳信号,本文提出了一种新的信号分析方法———广义解析模态分解（Generalized Analytical Mode Decomposition,GAMD）．GAMD通过广义傅里叶变换将时变频率转换为频谱可分的,采用解析模态分解对其分解,再对得到的单分量信号进行逆广义傅里叶变换即可得到原始信号的分量．因此,GAMD非常适合分析时变的非平稳信号．通过仿真信号将GAMD与短时傅里叶变换和希尔伯特黄变换等方法进行了对比,结果表明GAMD方法的分解效果更精确,时频分辨率更高．     

时频面滑窗掩膜的多分量信号高效重构算法

针对基于特征值分解的 Wigner-Ville 分布信号重构算法运算复杂度高这一问题,该文提出一种高效多分量信号重构算法。首先,通过分析 Wigner-Ville 逆变换公式,推导出瞬时时刻重构序列与原序列之间的联系,提出一种高效的信号重构算法。然后,采用平滑伪Wigner-Ville分布作为时频掩膜抑制Wigner-Ville分布的交叉项,并通过在时频面内滑窗的方法逐一提取各分量信号。最后,结合高效信号重构算法和时频面滑窗掩膜技术,实现多分量信号快速准确重构。仿真实验证明了该算法的有效性和可行性。     

常规时频分析方法对比分析研究

时频分析技术兼具时间域和频率域特性,它根据地震波在地下传播时衰减与频率相关以及油气对于频率的敏感性,利用时频分析技术将信号从时间域变换到频率域进行信号分析。文章阐述了时频分析技术中的短时傅里叶变换(STFT)、S变换(ST)、匹配追踪Wigner-Ville分布(MP-WVD)三种变换方法;对比三种方法,得出匹配追踪Wigner-Ville分布的时频变换方法兼具了时频原子的独立性和高时频分辨率的特性,在实际地震资料的时频分析中表现出了对信号的较高品质的时频表示。     

基于频域CLEANWigner-Ville分布中交叉项的抑制

针对ISAR飞机成像中出现的多分量线性调频(chirp)信号,该文提出一种基于频域CLEAN的信号分解方法,将其分解成多个单分量chirp信号,然后分别计算每个单分量的Wigner-Ville分布(WVD),以此来抑制此多分量信号WVD中的交叉项,与已有的chirp信号分解方法相比,该法减少了待估计参数的个数,使得计算更加简单,并能保证信号各分量正确的强度及时频变化特征。经过处理后的信号的WVD,保持了WVD高时频分辨率的特点,而交叉项得到了很好的抑制。实验表明,该方法应用于实测数据,成像质量明显提高了。     

强干扰下非平稳跳频信号高分辨测试技术研究

为了提高对强电磁辐射干扰下的非平稳跳频信号检测性能,提出一种基于时频分析的非平稳跳频信号高分辨测试技术.采用短时傅立叶变换构建非平稳信号的时频分析模型,把信号划分成许多小的时间间隔,在时间轴连续滑动窗口上对信号进行固有模态分解,提取非平稳跳频信号的Hilbert谱特征,谱特征有效反映了信号的幅值在整个频率段上随频率的变化情况,从而找出信号中跳变的频率分量,实现信号高分辨测试.仿真结果表明,采用该方法在强干扰条件下进行信号测试,信号输出的分辨能力较强,准确检测概率较高,性能优于传统方法.     

基于改进EEMD的穿墙雷达动目标微多普勒特性分析

穿墙雷达动目标探测中人的心跳、呼吸、手臂摆动等运动的微多普勒信号是非线性、非平稳信号,可以采用经验模式分解(EMD)对其进行时频分析。由于EMD分解存在模式混合问题,该文提出一种改进的整体平均经验模式分解(EEMD)方法,并将其应用于穿墙雷达人的运动微多普勒特性分析中,并且对分解后的每个本征模式函数(IMF)进行Hilbert-Huang变换(HHT),得到信号的时间-频率-能量谱。仿真数据和实验结果分析均表明,改进的EEMD方法不仅能够有效消除EMD中的模式混合问题,将人运动微多普勒信号中的不同频率尺度分解在不同的IMF中,而且还能够有效抑制原始信号中的噪声,提高信噪比,得到更精细、更清晰的时频分布。     

基于改进经验小波变换的时频分析方法及其在滚动轴承故障诊断中的应用

经验小波变换是最近提出的非平稳信号分析方法,针对其不足,提出了一种改进的经验小波变换方法;同时结合瞬时频率新定义,提出了一种非平稳信号时频分析新方法.该方法首先通过改进的经验小波变换将一个复杂的非平稳信号自适应地分解为若干个具有紧支集频谱的内禀模态函数之和;再通过对每个内禀模态函数进行解调,得到原始信号的时频分布.将提出的方法应用于滚动轴承试验数据分析,并将其与希尔伯特黄变换进行了对比,结果表明,论文提出的方法能够有效地诊断滚动轴承故障,且诊断效果优于希尔伯特黄变换方法.     

通信电源的EMC技术研究

从通信电源电磁骚扰的机理着手,分析了通信电源的开关电路及二极管的反向恢复时间引起的电磁骚扰。从减小搔扰源产生的搔扰信号,切断搔扰信号的传播途径,增强被搔扰体的抗搔扰能力三个方面分别提出相应的电磁抑制措施,讨论了电磁兼容设计中需要加以注意的有关问题。最后以车载通信电源为例,主要分析了在一个电源系统中多个子系统之间出现的电磁兼容问题,阐述了在设计时的基本思考及有关问题的解决方案。     

交互式多方位电视直播系统设计

在传统的电视直播中,虽然设置了许多摄像机位,但在绝大部分时刻只输出一路经导演选择某一机位的信号进行播出,这样就不能最大程度地利用多路摄像机位同时采集到的信息。本文介绍在新闻、体育比赛、文艺演出、科学探索等某些类型的电视节目直播中,可以采用交互式多方位电视直播的方式,同时播出几路不同机位的直播信号,并传输给电视观众。这些信号可以是经过导播选择过的,而解说或电话采访、字幕等将作为公共信号,叠加到不同机位的直播信号中。观众可以根据自己的喜好,自主选择某路信号进行观看,从而达到真正的多方位电视直播的目的,将更多的现场信息传输给观众,让观众有更好的现场感受。     

A novel high-speed interface circuit saving wiring equipment

A high-speed integrated interface circuit is described, which is capable of transmitting and receiving full duplex digital signals on a twisted pair line. Thus two independent messages may be transmitted on one line at the same time. A push-pull transmitter and a differential amplifier as receiver provide a common-mode rejection of more than 1 V in either the positive or negative direction. Output signals and input threshold are compatible with ECL F100K. Compared to conventional interface transceivers this approach has the following advantages: (1) the needed number of lines and connectors is halved; (2) only one type of circuit is necessary, because both transmitter and receiver are housed in one package; (3) the reduced number of line pins leaves space for more transceiver circuits in one package.     

Signal nonlinearity in fMRI: a comparison between BOLD and MION

In this paper, we introduce a methodology for comparing the nonlinearities present in sets of time series using four different nonlinearity measures, one of which, the "delay vector variance" method, is a novel approach to the characterization of a time series. It is then applied to examine the difference in nonlinearity between functional magnetic resonance imaging (fMRI) signals that have been recorded using different contrast agents. Recently, an exogenous contrast agent, monocrystalline iron oxide particle (MION), has been introduced for fMRI, which has been shown to increase the functional sensitivity compared with the traditional blood oxygen level dependent (BOLD) technique. The resulting fMRI signals are influenced by cerebral blood volume, whereas the more traditionally recorded BOLD signals are influenced not only by cerebral blood volume, but also by the cerebral blood flow and the metabolic rate of oxygen. The proposed methodology is applied to address the question whether this difference in the number of physiological variables is reflected in a difference in the degree of nonlinearity. We therefore analyze two sets of fMRI signals, one from a BOLD and the other from a MION monkey study with similar experimental designs. In the neuroimaging context, the proposed nonlinearity analyses are different from those described in the literature, since no a priori model is assumed: rather than pinpointing the source(s) of nonlinearity, nonparametric analyses are performed on BOLD and MION fMRI signals. Furthermore, we introduce a strategy for analyzing a population of fMRI signals, rather than focusing the analysis on one signal, as is traditionally done in the domain of nonlinear signal processing. Our results show that, overall, the BOLD signals are more nonlinear in nature than the MION ones, which is in agreement with current hypotheses.     

基于单个频点的水声信号盲源分离

该文提出基于单个频点的卷积信号盲源分离方法,利用该方法不但可以有效克服频域盲分离过程中排序不确定问题,而且在分离过程中,无需考虑幅度不一致问题。将该方法用于水声信号的盲分离,仿真结果表明基于单个频点盲源分离方法能够很好地分离水声卷积混合信号。与基于两个频点盲源分离方法相比较,其分离效果更优,并且能有效节省CPU运算时间,因而更适合于对信号进行实时处理。     

Optimal signal design for sequential signaling over a channel with feedback

Turin [1] has studied the problem of optimal sequential detection over a channel with feedback when the signals used are subject to peak and average power constraints. With special additional constraints on the signals he was able to obtain a series solution for the first passage probability density and hence find optimal signals when the ratio of peak power to average power was infinity or one. Horstein,[2] concurrently with this study, was able to find optimal signals for arbitrary ratios of peak to average power when the signals were subject to the same special constraints. This paper presents a simpler and more direct approach for obtaining optimal signals which minimize the expected time to decision for arbitrary peak power constraints and various average power constraints. Explicit closed form solutions are derived for the expected energies and times to decision without having to first obtain the probability distribution of the first passage time. No special constraints are required on the signals. For communication with white noise in the feedback link, optimal stationary signals are found for peak and average power constraints. It is shown that communication rates up to but strictly less than channel capacity are possible with noisy feedback. However, it is also noted that for the schemes considered here, the stationary signals and white noise in the feedback link imply infinite feedback power.     

图像在“信号与线性系统”中的妙用

“信号与线性系统”课程中信号的频谱分析是重点,也是学生学习的难点。本文首先利用一维信号说明信号时域波形与频谱中频率分量的对应关系;然后利用二维图像进一步验证。对比一维信号和二维图像的说明方法,可以明显地看到后者更加直观形象．也更利于学生理解频谱的概念。实践证明利用二维图像可以达到更好的教学效果。     

语音时长规整技术的研究回溯

语音时长规整技术是在不改变语音音调并保证良好音质的情况下,对语音进行一定的压缩或拉伸的技术。首先给出了语音时长规整技术的发展历程和主要实现方法,重点阐述了主要实现算法的原理,并仿真实现了适合实时处理的两种时域算法,比较分析了两种时域方法的效果。最后对语音时长规整技术进行了展望。     

Simulation of dynamic light scattering signal for ultrafine particles based on the exponential model

According to the autocorrelation function (ACF) of dynamic light scattering (DLS) signals, the exponential model used for scattering signal simulation can be established. Based on this model, nine kinds of DLS signals for unimodal, bimodal and trimodal distribution particles are simulated respectively. The ACF of the simulated signal agrees with its theoretical value very well. Inverted size errors of simulative signals for unimodal distribution particles by Cumulants method and those for bimodal and trimodal distribution particles by nonnegative constraint least squares (NNLS) are less than 0.13%, 2.11% and 3.01%, respectively. Comparing the exponential model with autoregressive (AR) model, the calculation time of the former is less than one tenth of the latter. Hence, the exponential model is more effective in the simulation of DLS signals.     

Phased-array beam steering by multiplex sampling

One approach to phased-array antenna beam forming and steering is to multiplex the element signals into a single channel. Appropriate "sampling" of the resulting multiplexed signal can provide electronically steered and shaped beams. This paper describes four practical system concepts for linear and ring arrays based on this approach and discusses significant interrelationships between the various concepts. For linear arrays of elements, the two alternatives are to frequency or time multiplex the element signals. Frequency multiplexing of the element signals produces time-multiplexed beam output signals, and time multiplexing the element signals produces frequency-multiplexed beam output signals. It is also shown here that appropriate correlation "sampling" may be used with either of these to produce easily one or more continuously and electronically steered signal bandwidth beam outputs. Ring arrays of elements may be multiplexed and "sampled" in a somewhat analogous pair of techniques. It is also pointed out that the beam steering in this case may be visualized as the linear phase steering of a set of linear phase modes into which the signal received at the array may be resolved. Ring array beam forming and steering may thus be directly understood in terms of the previous linear array techniques.