基于变分模态分解-传递熵的脑肌电信号耦合分析

皮层肌肉功能耦合是大脑皮层和肌肉组织间的相互作用, 脑肌电信号的多尺度耦合特征可以体现皮层-肌肉间多时空的功能联系. 本文引入变分模态分解并与传递熵结合, 构建变分模态分解-传递熵模型应用于脑肌间耦合研究. 首先基于变分模态分解将同步采集的脑电(EEG) 和肌电(EMG) 信号分别进行时频尺度化, 然后计算不同时频尺度间的传递熵值, 获取不同耦合方向(EEG→EMG 及EMG→EEG) 上不同尺度间的非线性耦合特征. 结果表明, 在静态握力输出条件下, 皮层与肌肉beta (15—35 Hz) 频段间的耦合强度最为显著; EEG→EMG 方向上脑电与肌电高gamma (50—72 Hz) 频段的耦合强度总体上高于EMG→EEG 方向.研究结果揭示皮层-肌肉功能耦合具有双向性, 且脑肌间不同耦合方向上、不同频段间的耦合强度有所差异.因此可利用变分模态分解-传递熵方法定量刻画大脑皮层与肌肉各时频段之间的非线性同步特征及功能联系.     

基于多类运动想象任务的EEG信号分类研究

针对多类运动想象脑电信号个体差异性强和分类正确率比较低的问题,提出了一种时-空-频域相结合的脑电信号分析方法：首先利用小波包对EEG原始信号进行分解,根据EEG信号的频域分布提取出运动想象脑电节律,通过“一对多”共空间模式（CSP）算法对不同运动想象任务的脑电节律进行空间滤波提取特征;然后将特征向量输入到“一对多”模式下的支持向量机（SVM）中,并利用判断决策函数值的方法对SVM的输出结果进行融合;最后通过引入时间窗对脑电信号进行时域滤波,消除运动想象开始和结束时脑电的波动,进一步提高信号信噪比和算法的分类效果。实验结果显示：在时间窗为2s时,平均最大 系数达到了0.72,比脑机接口竞赛第一名提高了0.15,验证了该算法能够有效减小脑电信号个体差异性影响,提高多类识别正确率。     

水下高速小目标探测中的信号波形设计研究

探讨水下高速小目标探测中的声呐信号波形设计问题,指山在混响信道和多途传播信道中适宜的信号形式是多频的时频跳变信号,并给出了抗混响的频率选择方法.要达到目标参数的精确估计,信号必须具有时频的高分辨性能.信号分析结果表明,频率序列满足Costas阵列的时频跳变信号具有尖锐的模糊度指向性,可以用在探测水下高速小目标的有源声呐系统中。     

基于弹性变分模态分解的癫痫脑电信号分类方法

癫痫脑电信号分类对于癫痫诊治具有重要意义.为了实现病灶性与非病灶性癫痫脑电信号的分类,本文利用弹性网回归重构变分模态分解算法,提出弹性变分模态分解算法并将其应用到所提癫痫脑电信号分类方法中.该方法先将原信号分割成多个子信号,并对各子信号进行弹性变分模态分解,然后从分解后的不同变分模态函数中提取精细复合多尺度散布熵作为特征,最后利用支持向量机进行分类.针对癫痫脑电的公共数据集,最终的实验结果表明,准确率、灵敏度和特异度三个性能指标分别达到92.54%,93.22%和91.86%.     

Time-frequency analysis and modeling of the backscatter of categorized dolphin echolocation clicks for target discrimination

A set of dolphin echolocation clicks collected from an Atlantic bottlenose dolphin in Kaneohe Bay, Hawai'i from a previous experiment is examined in terms of their time and frequency characteristics. The center frequency and rms bandwidth are calculated for the clicks and these are clustered into four classes by using a model based on the Bayesian information criterion. The echo signatures are attained from a solid, elastic homogeneous sphere for each class of clicks from an acoustic scattering model. The results from the scattering model are compared to experimental values. The joint time-frequency content of the resulting echo signals is obtained by the reduced interference distribution (RID). The RIDs are plotted and examined for each signal class for four spherical targets of different material compositions. RID correlation values are obtained for a standard target versus comparison targets by using a time-frequency correlator. The results suggest that dolphins may discriminate by auditory inspection of the time-frequency information returned by the targets. The modification of the outgoing clicks and examination of time-frequency target information may be fundamental to a dolphin's ability to identify and discriminate targets.     

Analysis of underwater mammal vocalisations using time-frequency-phase tracker

One of the most challenging applications of time-frequency representations deals with the analysis of the signal issued from natural environment. Recently, the interest for passive underwater context increased, basically due to the rich information carried out by the natural signals. Taken into account the non-linear multi-component time-frequency behaviour of such signals, their analysis is a challenging problem.In this context, the analysis of underwater mammal’s whistles is aimed to extract, accurately and adaptively, their main time-frequency components. In this paper, we define a time-frequency-phase tracker which is composed of three steps. The first one consists of modelling the short-time segments of the vocalization by a set of third order polynomial phase modulations. The second step consists in the fusion of local polynomial phase modulations according to a local phase continuity criterion. Finally, in the third step, the detected time-frequency track is used to design the time-frequency filter, in charge of extracting the samples corresponding to the detected track. This procedure is then iterated until all component of interest are extracted.Tests provided for realistic scenarios and real data taken in Bay of Biscay at September 2009 containing whistles of common dolphin Delphinus delphis illustrate the potential and the benefits of the proposed approach.     

基于超声回波重组相位分析的颗粒粒径测量方法

将超声波作用于沉降的颗粒时,由于颗粒的移动,超声回波会出现相位差异。该文通过对测量杯中某一确定深度处的回波信号进行相位分析和重组,发现重组后信号的频率可以计算出粒径;并分别对两种不同粒径分布的聚甲基丙烯酸甲酯(PMMA)微球悬浮液进行了超声波信号采样重组和去噪的实验,实验结果经小波时频方法分析后,证实了颗粒粒径分布与重组信号频率构成的确存在很高的相关性。     

基于频率切片小波变换和支持向量机的癫痫脑电信号自动检测

实现癫痫脑电信号的自动检测对癫痫的临床诊断和治疗具有重要意义.本文提出先使用频率切片小波变换分离出5个不同频段的节律信号,再分别计算每个节律信号的近似熵和相邻节律的波动指数,最后使用遗传算法优化的支持向量机进行分类.实验结果表明,所提出的方法能够对正常、癫痫发作间期和癫痫发作期三种脑电信号进行准确分类,分类准确率为98.33%.     

宽带双曲调频信号参数化时频分析波达方向估计

针对有源探测或脉冲侦查中双曲调频信号的波达方向估计问题,提出了基于参数化时频变换(PTFT)的多重信号分类(MUSIC)测向算法,简称PTFT-MUSIC算法。该算法由发射信号确定针对双曲调频信号的参数化变换核,对接收信号进行频域参数化时频变换,利用获得的时频分布建立阵列信号时频分布模型,并以此模型设计基于时频分布矩阵的MUSIC算法以实现双曲调频信号的波达方向估计。通过仿真和实验对该算法的估计误差和多目标分辨性能进行了分析,仿真和海上实验结果表明:相比现有的时频MUSIC算法,PTFT-MUSIC算法能有效提高空间谱分辨率和波达方向估计性能,同时该算法拥有对特定调频信号筛选性,结合时频域滤波算法能有效抑制相干直达波干扰,应用于多基地声呐系统时有效提高了声呐定位性能。     

基于EMD的谱峭度方法在滚动轴承故障检测中的应用

传统谱峭度方法通常采用基于短时傅里叶变换(Short Time Fourier Transform,STFT)的峭度图方法来实现。针对STFT不能保证对瞬态脉冲这种高度非平稳信号最优的分解效果的缺点,提出一种基于经验模式分解(Empirical Mode Decomposition ,EMD)的谱峭度方法。该方法首先利用EMD和Hilbert变换得到信号的时频分布,然后将信号的时频分布按照不同层数分成若干频段,通过计算各频段的峭度值得到相应的峭度图,再根据峭度最大原则选择滤波频段进行带通滤波,最后对滤波信号采用包络分析确定故障信息。实验结果表明：相比传统基于STFT的谱峭度方法,本文方法更能准确的获得轴承加速度信号的故障特征频率信息。     

基于时频分析的多目标盲波束形成算法

针对现有盲波束形成算法适用范围较窄, 多目标信号分离级联模式结构复杂、并联模式稳定性较差等问题, 提出一种基于时频分析的多目标盲波束形成算法. 该算法首先利用时频分析技术给出信号导向矢量的不确定集, 然后优化求解导向矢量的最优估计, 最后利用Capon方法实现多目标信号的并行输出. 理论分析及仿真结果表明, 该算法对信号特性没有特殊要求, 适用性较广, 性能稳定, 且输出信干噪比高于其他盲波束形成算法, 接近于最优Capon波束形成器.     

可调谐半导体激光器的瞬时光谱测量方法研究

可调谐半导体激光器在调谐过程中的瞬时光谱特性,如瞬时的波长、调谐率、功率、线型和线宽等参数影响着以激光器为光源的光学测量和光相干通信系统的精度。然而,能够同时测量这些瞬变参数的技术至今未见报道。提出了一个基于时频分析的测量半导体激光器在调谐过程中瞬时光谱参数的方法,利用一个短时延外差测量系统,利用激光器瞬时光谱参数与差拍信号瞬时参数的关系,最终获得了半导体激光器在连续电流调谐过程中的瞬时光谱。测量系统采用了10 cm光程差的Mach-Zehnder干涉仪,调谐电流是幅度为20~120 mA、频率是1 kHz的锯齿波,差拍信号可视为直流信号、载波信号与噪声的叠加,按照短时延相干光测量原理,差拍信号中的直流分量幅度的大小反映了激光器输出光信号的功率;载波信号是一种多项式相位信号,由其频率可以推算激光器输出光谱的中心频率或波长;噪声信号则与激光器输出光谱的线型和线宽相关,通过对噪声信号进行时频分析,可以获知激光器在连续电流调谐过程中每一时刻或每个电流下的瞬时线型、线宽。采用了趋势局部均值分解方法对差拍信号进行了准确分离,并对分离信号分别进行处理,同时获知了半导体激光器在调谐过程中的瞬时输出光功率、光波长、调谐率及线型、线宽。在去掉弛豫部分后截取的整周期差拍信号对应的调谐电流60~115 mA变化范围内,半导体激光器(FRL15DDR0A31-18950, Furukawa)瞬时输出光功率变化范围是5.16~10.6 mW,瞬时光波长变化范围为1 579.2~1 579.6 nm;激光器的瞬时调谐率在0.004 8~0.011 5 nm·mA-1范围内单调变化;线宽是852.55~954.95 kHz,呈非线性随机分布。基于短时延、局部均值分解和时频分析方法的瞬时光谱参数测量系统可以准确得到各瞬时光谱参数,测量结果与激光器的静特性相符,且测量系统结构简单,使我们更深入地理解激光器的工作原理,具有广阔的应用前景。     

Experimental studies on sound and vibration of a two-tone Chinese Peace Bell

In order to examine whether the characteristics of the bell are coincident with the design and make some constructive suggestions for the tuning of bell, the frequency characteristics of sound and the vibrational modes of a two-tone Chinese Peace Bell have been studied. With Welch's spectral estimate, the main partials of radiated sound of the bell have been found out. With time-frequency analysis, the changes of the spectrum with time have been shown. By conditional mean frequency (CMF) of the spectrogram of the sound, the change in the pitch of the bell has been discussed. With an accelerator, the vibration distributions on the different points of the bell have been measured. With short time spectrum analysis, the vibrational modes at different frequencies have been reconstructed.     

Pulse amplification characteristics of multimode fiber amplifier

Under small signal situation, the analytical expression for describing the output signal emitted from an Yb³⁺-doped fiber amplifier with a Gaussian input pulse signal is deduced, by full considering both fiber guided modes’ propagation constant and filling factor, which depend on the signal frequency. Pumped by continue wave (CW) source, the analytical expressions of the small signal gain and each guided mode's output power are obtained. Based on these analytical expressions, the various intensity distributions of output pulses amplified by the fiber amplifier with different Gaussian input pulse widths are analyzed.     

基于多项式调频Fourier变换的信号分量提取方法

为了从含有噪声的混合信号中有效提取各个信号分量, 提出一种基于多项式调频Fourier变换的分量提取方法. 通过研究Fourier变换和分数阶Fourier变换的信号能量积累方式及变换基函数的时频表示, 提出利用时频平面上的多项式调频曲线族代替Fourier变换和分数阶Fourier 变换的调频直线族, 将变换的适用范围扩展到非线性调频信号. 采用粒子群智能优化算法搜索调频曲线族的最优多项式参数, 使混合信号中的某一分量在多项式调频Fourier域上能量谱集中. 最后对能量谱集中的分量进行窄带滤波, 并利用多项式调频逆Fourier变换重构信号分量. 仿真实验结果表明, 该方法不仅能够提取混合信号中的线性调频分量, 还能够实现非线性调频分量的能量谱集中、信号分离和时频特征提取.     

A class of asymmetric pathway distributions and an entropy interpretation

Asymmetric distributions are widely used in probability modeling and statistical analysis. Recently, various asymmetric distributions are being developed by many researchers for modeling various data sets in real life contexts. In the present paper, we introduce a new class of q-type asymmetric distributions which include q-analogues of asymmetric Laplace, exponential power, Weibull etc. and corresponding standard distributions as special cases. Also we show that this pathway model can be obtained by optimizing Mathai’s generalized entropy with more general setup, which is a generalization of various entropy measures due to Shannon and others.     

Instantaneous frequency decomposition: an application to spectrally sparse sounds with fast frequency modulations

Classical time-frequency analysis is based on the amplitude responses of bandpass filters, discarding phase information. Instantaneous frequency analysis, in contrast, is based on the derivatives of these phases. This method of frequency calculation is of interest for its high precision and for reasons of similarity to cochlear encoding of sound. This article describes a methodology for high resolution analysis of sparse sounds, based on instantaneous frequencies. In this method, a comparison between tonotopic and instantaneous frequency information is introduced to select filter positions that are well matched to the signal. Second, a cross-check that compares frequency estimates from neighboring channels is used to optimize filter bandwidth, and to signal the quality of the analysis. These cross-checks lead to an optimal time-frequency representation without requiring any prior information about the signal. When applied to a signal that is sufficiently sparse, the method decomposes the signal into separate time-frequency contours that are tracked with high precision. Alternatively, if the signal is spectrally too dense, neighboring channels generate inconsistent estimates-a feature that allows the method to assess its own validity in particular contexts. Similar optimization principles may be present in cochlear encoding.     

基于频散特征的单水听器模式特征提取及距离深度估计研究

针对浅海环境中低频宽带水声脉冲信号, 研究基于频散特征结合时频分析的单水听器距离和深度估计方法. 以简正波理论为依据, 将单水听器上的接收信号表示成一系列传播模式之和的形式, 分析了经典波导环境下的频散现象, 采用自适应径向高斯核函数的时频分析方法来表征接收信号的频散特征. 为提高时频分辨率, 采用自适应径向高斯核函数的时频分布来提取频散关系曲线中传播模式的到达时间差, 利用模式的到达时间差估计声源的距离. 采用多模式联合匹配的方式, 通过二值掩模滤波的时频滤波方法, 提取所需的模式. 通过计算实际提取出的模式能量与预测的模式能量之间的误差, 建立代价函数, 并通过模式能量匹配的方式, 确定声源的深度. 通过对基于Pekeris波导模型的浅海环境进行仿真验证, 结果表明: 自适应径向高斯核函数的时频分析方法能够很好地反映信号本身的频散特征, 具有较高的时频分辨率, 克服了传统短时傅里叶变换时频表征的限制, 使得模式在时频域更加容易辨识和分离; 从测距效果来看, 不同模式组合下的距离估计结果不同, 采用在时频面上具有较高能量的模式, 可得到较为准确的距离估计; 选用高能量的模式所得的距离估计的相对误差小于2%. 在定深方面, 参与联合匹配的模式个数越多, 代价函数的峰值更加地尖锐, 同时具有低的伪峰, 深度估计的性能会进一步有所提升. 该工作对于研究低频水声脉冲信号的分离和提取具有重大意义. 关键词： 频散信道 时频分析 单水听器 定位     

Estimation of ultrasound attenuation and dispersion using short time Fourier transform

Determination of the acoustic attenuation and dispersion has important applications in ultrasound tissue characterization and non-destructive material testing. Current signal processing methods Fourier transform of ultrasound signals to get the spectra of amplitude and phase to estimate respectively the attenuation and dispersion of a given medium. These methods are frequency domain method and obsessed with ambiguity issue in the phase unwrapping calculation. Conventional ultrasound velocity measuring method detects the time of arrival of a pulse (or echo) signal, which is a time domain method to compute group velocity (not phase velocity). This paper presents a novel approach based on the short time Fourier transform (STFT)--a time-frequency analysis, to estimate the ultrasonic dispersion and attenuation. Only the amplitude information of the pulse-signal spectra is used. Based on the time-frequency presentation, the attenuation coefficient of the signal is obtained by computing the amplitude decay of pulse spectrum in time domain, while phase velocities are obtained based on the "time-of-flight" (TOF) of the mono frequency component of the pulse signals. As a result, we eliminate the ambiguity issue in phase angle calculation. Furthermore, the proposed method makes the phase velocity pedagogically intuitive for novice users. The paper presents experiments to evaluate demonstrate the performance of the proposed method.     

Characterization of the train-average time-frequency parameters inherent in the low-power picosecond optical pulses generated by the actively mode-locked semiconductor laser with an external single-mode fiber cavity

The specific approach to characterizing the train-average parameters of low-power picosecond optical pulses with the frequency chirp, arranged in high-repetition-frequency trains, in both time and frequency domains is elaborated for the important case when the semiconductor laser is matched by an external single-mode fiber cavity and operates in the active mode-locking regime. This approach involves the joint Wigner time-frequency distributions, which can be created for those pulses due to exploitation of a novel interferometric technique. Practically, the InGaAsP/InP-heterolaser generating at the wavelength 1320 nm was used during the experiments carried out and an opportunity of reconstructing the corresponding joint Wigner time-frequency distributions was successfully demonstrated.