Harmonic Retrieval Embedded in Hybrid Colored Noise: a Novel Pisarenko Method Based on Cross high order Cumulant

Spectral estimation method is an effective method in the case of parameter estimation of sinusoid signal in noises.It always applies cross spectral estimation theory and high order self spectral estimation methods up to now.Yule Walker equation based on cross fourth order cumulant is developed and Pisarenko method is provided in this paper.Simulation results show that the method is effective to retrieve sinusoid signal frequencies from hybrid colored noises and has good performance.

Signal Classification Method Based on Support Vector Machine and High-Order Cumulants

In this paper, a classification method based on Support Vector Machine (SVM) is given in the digital modulation signal classification. The second, fourth and sixth order cumulants of the received signals are used as classification vectors firstly, then the kernel thought is used to map the feature vector to the high dimensional feature space and the optimum separating hyperplane is constructed in space to realize signal recognition. In order to build an effective and robust SVM classifier, the radial basis kernel function is selected, one against one or one against rest of multi-class classifier is designed, and method of parameter selection using cross- validation grid is adopted. Through the experiments it can be concluded that the classifier based on SVM has high performance and is more robust.

Recognition Analysis and Simulation Implementation Based on High-Order Cumulants of Wireless Digital Modulation Mode

This paper mainly studies the data characteristics of high order cumulants using digitally modulated signals, and constructs the identification feature parameters that can distinguish the signal modulation type by the high-order cumulants data of the digital modulation signal. Set the identification signal modulation type determination threshold based on the value of the identification feature parameter. The identification feature parameter value of the signal modulation type is compared with the set determination threshold, to realize the recognition of digital modulation signal. This identification method is implemented based on MATLAB design, with a 2ASK (2-ary Amplitude Shift Keying) signal, 4ASK (4-ary Amplitude Shift Keying) signal, 2PSK (2-ary Phase Shift Keying) signal, 4PSK (4-ary Phase Shift Keying) signal, 2FSK (2-ary Frequency Shift Keying) signal, 4FSK (4-ary Frequency Shift Keying) signal. The second, fourth and sixth order cumulants of the six signals were analyzed. Calculate the selected identification feature parameter value and the determination threshold to identify the six signals. The six signals have made MATLAB identification simulation. Simulation results show that this method is feasible and has high recognition rate. Simulation results verify that such recognition methods maintain a high recognition rate under conditions with low signal-to-noise ratio. This identification method can be extended to more MASK (M-ary Amplitude Shift Keying), MPSK (M-ary Phase Shift Keying), MFSK (M-ary Frequency Shift Keying), MQAM (M-ary Quadrature Amplitude Modulation) signal identification.

A MODIFIED HIGH-ORDER CUMULANT MUSIC ALGORITHM FOR SIGNAL DOA ESTIMATION

This paper gives a MUSIC signal DOA estimation algorithm based on the modified high-order cumulant matrix which is constructed by the recieved data and their conjugate rearrangements. When the snapshot number is limited, this algorithm can improve the signal DOA estimation performances obviously, and its computational complexity scarcely increases. Finally, some simulation results to verify the theoretical analyses are presented.

THE FOURTH-ORDER CUMULANTS BASED SPECTRALESTIMATION METHOD AND ITS APPLICATIONTO DIRECTION-FINDING

Traditional approaches of spatial spectral estimation are usually based on the second-order statistics. The higher-order cumulants and the poly-spectrum contain more information and are capable of reducing the Gaussian noise. In this paper, we present a new spectrum estimation method for direction-finding, the FOMUSIC algorithm, which is based on the eigen-structure analysis of the fourth-order cumulants. The derivation of the algorithm is given in detail and its performance is illustrated by both the computer simulations and the experiments of a direction-finding system. The obtained results demonstrate that the fourth-order cumulants based method outperforms the traditional methods, especially when the noise is an unknown colored one.

Cross-phase modulation instability in optical fibres with exponential saturable nonlinearity and high-order dispersion

Utilizing the linear-stability analysis, this paper analytically investigates and calculates the condition and gain spectra of cross-phase modulation instability in optical fibres in the ease of exponential saturable nonlinearity and high-order dispersion. The results show that, the modulation instability characteristics here are similar to those of conventional saturable nonlinearity and Kerr nonlinearity. That is to say, when the fourth-order dispersion has the same sign as that of the second-order one, a new gain spectral region called the second one which is far away from the zero point may appear. The existence of the exponential saturable nonlinearity will make the spectral width as well as the peak gain of every spectral region increase with the input powers before decrease. Namely, for every spectral regime, this may lead to a unique value of peak gain and spectral width for two different input powers. In comparison with the case of conventional saturable nonlinearity, however, when the other parameters are the same, the variations of the spectral width and the peak gain with the input powers will be faster in case of exponential saturable nonlinearity.

Higher Order Moment Spectra Time-Frequency Analysis of the Geophysical Signal

On the basis of an introduction of the Wigner Higher-Order spectra (WHOS) and a general class of time-frequency higher-order moment spectra, the geophysical signal was analyzed using the higher order time-frequency distributions (TFD). Simulation results obtained in this paper show that the higher-order TFD (Wigner Bispectrum, Wigner Trispectrum and Choi-Williams Trispectrum) have much better Time-Frequency Concentration than the second-order TFD, and the reduced interference higher-order TFD such as CWT can effectively reduce the cross-term in multicomponent signals and simultaneously obtain high time-frequency concentration.

基于高阶累积量ESPRIT算法的指数衰减正弦信号参数估计

工程应用中环境噪声多表现为高斯有色噪声,而针对高斯白噪声进行处理的算法失效问题,提出了一种高斯色噪声环境中用于多分量衰减正弦信号频率和衰减因子估计的四阶累积量ESPRIT算法。首先,推导出四阶累积量与观测样本中的自相关矩阵和互相关矩阵之间的关系,求出其四阶累积量矩阵。其次,通过对四阶累积量进行广义特征值分解,根据广义特征值即可得到信号衰减因子和频率的估计值。最后对所提算法进行了仿真实验验证,在混合信噪比为0 dB时,所提算法针对多分量衰减正弦信号角频率和衰减因子的平均估计误差分别为0.002 0πrad和0.002 0。在高斯白噪声和高斯色噪声背景下与ESPRIT算法和Prony算法相比具有更强的噪声抑制能力和更高的估计精度。

基于谱线-高阶累积量的调制识别研究与实现

已发表的调制识别算法大多基于单一特征参数,识别种类较少,且往往很难在实际系统中布署。提出了一种基于谱线-高阶累积量的数字调制识别算法,该算法利用载波频率估计、符号速率估计、定时恢复、噪声功率估计等前处理手段,结合信号功率谱、二次方谱、四次方谱中的离散谱线和四阶归一化高阶累积量,可识别2ASK、4ASK、8ASK、2FSK、4FSK、8FSK、BPSK、QPSK、8PSK、OQPSK、MSK、16QAM、32QAM、64QAM、128QAM、256QAM 16种数字调制信号。基于该算法,设计并实现了一种数字调制识别处理系统,可实时识别上述16种调制信号。结果表明,该实时系统对大部分调制信号的识别准确率可达到99%以上,对8PSK、32QAM、128QAM等调制信号的识别准确率可达到94%以上。

考虑新能源高阶不确定性的交直流混联电网静态电压稳定裕度计算

随着大量新能源场站接入交直流混联电网,系统的静态电压稳定裕度(static voltage stability margin,SVSM)水平具有很大的不确定性,需要研究考虑新能源场站高阶不确定性的交直流混联电网SVSM计算方法。针对此问题,首先建立了交直流混联电网SVSM计算模型,模型中考虑了直流换流站控制方式随负荷增长的切换;采用概率盒模型描述风速与光照强度的随机波动,提出了改进区间半不变量法以获得更准确的SVSM概率盒,该方法通过K-means++聚类算法将随机变量样本划分为多个波动范围较小的样本集,以降低半不变量的线性化计算带来的误差;并结合Gram-Charlier级数展开和概率加权和计算得到考虑新能源场站高阶不确定性的系统SVSM概率盒。通过对修改的IEEE-39节点交直流系统和南方电网两个算例的分析,并与区间半不变量法和双层蒙特卡洛法比较,验证了所提出方法获得的SVSM概率盒具有较高的计算精度和效率。

模体感知的自适应跨层游走社区检测

近年来,利用高阶交互信息进行多层网络社区检测已成为复杂网络分析领域的研究热点。尽管多层网络社区检测的研究已取得了一些进展,但大多数方法忽略了网络各层之间的联系。为了解决这一问题,提出了一种模体(motif)感知的自适应跨层游走社区检测算法(Motif-aware Adaptive Cross-Layer random walk Community Detection,MACLCD)。该算法充分考虑了多层网络各层内的高阶交互特性以及层间的相关性,有效整合了多层网络的结构信息,提高了社区检测结果的准确性。具体地,首先从网络和节点的角度进行综合度量,揭示网络层间相关性;其次,考虑了各层网络可能具有不同的局部和全局结构特征,利用motif识别各层网络特有的高阶交互结构,构建多层加权混合阶网络;进一步,设计了多层网络跨层游走模型,并引入跳转因子,以确保随机游走能够自适应地遍历多层网络,从而捕获更丰富的网络结构信息。在4个真实的网络数据集上进行实验比较分析,结果表明MACLCD算法在社区检测方面性能较优,相比目前表现最佳的对比算法在ACC和NMI上分别提高了10%和8.9%。

基于高阶累积量的变压器多局放源定位算法研究

变压器内部局部放电源的定位是电气设备绝缘领域所面临的技术难题。本文中作者研究了一种用于检测电力变压器局部放电的L字型超声阵列,传感器由7阵元L字形超声波传感器构成。通过高阶累积量的孔径扩展特性对L字型阵列进行虚拟扩展,使扩展后的阵列具有16阵元平面阵列的估计性能,提升了阵列的估计范围,降低了电路的复杂度,减少了硬件成本。通过试验验证了该算法具有与经典MUSIC算法4×4平面阵列DOA效果相当的估计效果,并在高斯色噪声的背景下对比了MUSIC-LIKE算法与MUSIC算法的估计效果,结果显示MUSIC-LIKE算法在相同条件下具有更好的估计精度,能够较好的抑制高斯色噪声干扰,更符合实际工程情况的应用。

基于FACAM-Efficient Net的通信信号调制方式识别

针对在复杂电磁空间中,通信信号识别方法存在噪声干扰、识别率不足、网络模型复杂等问题,提出基于高阶累积量可视化时频图像的FACAM-Efficient Net信号调制方式识别方法,通过高阶累积量时频分析方法,将不同调制的通信信号转换成可视化时频图像,用作网络模型的训练和测试,根据可视化时频图像的图像特征,提出FACAM频域通道混合注意力机制,并引入FACAM改进Efficient Net的网络主体结构,更好地提取时频图像的频域和通道的特征。实验结果显示,本文提出的调制识别方法在低信噪比下有较好的识别效果。

NOMA系统下基于高阶累积量的叠加信号调制识别

为解决非正交多址系统中的信号调制识别问题,利用高阶累积量的特性,提出了一种基于高阶累积量的调制识别算法,主要包含特征提取、概率密度函数构建和信号分类三个模块。仿真结果表明,与已有算法相比,所提出的基于高阶累积量的调制识别算法,在中低信噪比下可有效改善系统的识别性能。最后,利用浮点数计算了所提出算法的复杂度,结果表明该算法相较传统的最大似然检测算法复杂度大大降低,证明了该算法的有效性。

Scheimpflug imaged corneal changes on anterior and posterior surfaces after collagen cross-linking

AIM:To compare the anterior and posterior corneal parameters before and after collagen cross-linking therapy for keratoconus.METHODS:Collagen cross-linking was performed in31 eyes of 31 keratoconus patients(mean age 30.6±8.9y).Prior to treatment and an average 7mo after therapy,Scheimpflug analysis was performed using Pentacam HR.In addition to corneal thickness assessments,corneal radius,elevation,and aberrometric measurements were performed both on anterior and posterior corneal surfaces.Data obtained before and after surgery were statistically analyzed.RESULTS:In terms of horizontal and vertical corneal radius,and central corneal thickness no deviations were observed an average 7mo after operation.Corneal higher order aberration showed no difference neither on anterior nor on posterior corneal surfaces.During follow-up period,no significant deviation was detected regarding elevation values obtained by measurement in mm units between the 3.0-8.0 mm-zones.CONCLUSION:Corneal stabilization could be observed in terms of anterior and posterior corneal surfaces,elevation and higher order aberration values 7mo after collagen cross-linking therapy for keratoconus.

Frequency Domain TOA Estimation Algorithm Based on Cross-HOC

High-Order Cumulants(HOC)and cross-correlation was combined to suppress the Gaussian color noises and the un-related noises in real applications.The cross-HOC TOA estimation model was developed based on the diagonal slice of the forth-cross-cumulant.The eigen analysis was carried out,and the eigen noise space and the eigen signal space was achieved.Then the Frequency Domain TOA estimation algorithm based on Cross-HOC was developed.Different simulation experiments were carried out to draw out the conclusions.

基于过零检测的Buck变换器自适应连续滑模控制

为提高Buck变换器的输出电压品质,本文提出一种基于在线过零检测自适应机制的连续滑模控制方法,可有效抑制抖振问题,且可保证系统稳态误差收敛到给定范围.本文建立变换器的数学模型,从滑模面和控制律两方面改进传统滑模控制算法,即有目的地将系统状态的积分项引入到滑模面的设计中,并将其收敛轨迹分成两阶段,实时测量其过零点的个数;将期望的稳态误差纳入到滑模控制律的设计中,引入由系统状态过零点个数决定的自适应变增益,在收敛轨迹的约束下,分阶段推导出其变增益的连续控制律,并给出相应的稳定性分析.最后,通过与传统一阶和二阶滑模的理论和仿真性能对比,证明所提方法在抖振抑制、响应速度和控制精度方面的优越性.

基于连续交叉小波相干分析和自适应CYCBD的轴承故障诊断

最大二阶循环平稳指标盲解卷积(maximum second-order cyclostationarity blind deconvolution,CYCBD)能从强背景噪声信号中恢复周期脉冲,是轴承故障诊断的有效方法。故障特征频率是CYCBD的关键参数,由于滚动轴承存在制造误差、滚子滑移等现象,导致真实的故障特征频率与理论值存在偏差,降低了CYCBD的有效性。同时,故障轴承测试信号中含有大量噪声和谐波干扰,也降低了CYCBD的故障特征提取能力。对此,提出了一种基于连续交叉小波相干分析和自适应CYCBD的轴承故障诊断方法,首先,利用正常轴承、故障轴承测试信号的交叉小波相干分析获取轴承故障共振频带。其次,基于3种归一化的周期检测指标提出一种新的周期检测技术以获取真实的轴承故障特征频率。最后,基于轴承故障共振频带信号和真实轴承故障特征频率进行CYCBD滤波,并针对滤波信号进行Teager能量算子解调分析得到能量频谱,从而进行轴承故障诊断。仿真信号和高速列车牵引电机轴承试验信号的分析结果表明,该方法能够有效识别轴承故障特征,且优于传统的CYCBD方法。

改进粒子群优化超限学习机的调制信号识别

针对现有算法在信噪比较小条件下对调制信号识别精度较差的问题,提出一种基于改进粒子群优化超限学习机的调制信号识别算法。以调制信号的高阶累积量为基础构建4种特征参数,并根据多进制相移键控(Multiple Phase Shift Keying,MPSK)信号的相位特性引入归一化瞬时相位平均值和递归归一化瞬时相位平均值特征两个特征参数,构建调制信号的6种特征参数的数据集。利用粒子群优化(Particle Swarm Optimization,PSO)算法优化超限学习机(Extreme Learning Machine,ELM)算法的神经网络结构,动态调整PSO算法中的惯性权重,以提升算法的识别性能。采用所提算法对7种调制信号进行识别,实验结果表明,当信噪比大于2 dB时,所提算法对7种调制信号的识别正确率均达到100%。与相关算法相比,所提算法的识别效果较佳且更具有稳定性。

基于主成分分析的圆角截面薄壁梁一维高阶动力学建模方法

基于一维高阶理论和模式识别算法,建立了考虑圆角截面特征的薄壁梁精细动力学模型,能够准确预测其三维动力学行为。构建基于离散薄壁截面基函数的一维高阶初始模型,通过求解控制微分方程相关的广义特征值问题解耦各广义坐标的轴向变化模式。构建广义特征矩阵并基于主成分分析算法获取基函数权值组合,用于重组具有明确物理意义的截面特征形变组合。为进一步降低模型自由度,根据精度需求按优先级顺序选取截面特征形变组合,构建改进的一维高阶模型用于工程计算。数值计算结果表明,与二维板壳模型相比,该改进模型能够以前者1%的单元数准确预测圆角截面薄壁梁动力学特性及瞬态动力学行为,前15阶频率误差在1.4%以内,且能够广泛适用于长细比4以上的薄壁结构。