Application of local polynomial estimation in suppressing strong chaotic noise

In this paper, we propose a new method that combines chaotic series phase space reconstruction and local polynomial estimation to solve the problem of suppressing strong chaotic noise. First, chaotic noise time series are reconstructed to obtain multivariate time series according to Takens delay embedding theorem. Then the chaotic noise is estimated accurately using local polynomial estimation method. After chaotic noise is separated from observation signal, we can get the estimation of the useful signal. This local polynomial estimation method can combine the advantages of local and global law. Finally, it makes the estimation more exactly and we can calculate the formula of mean square error theoretically. The simulation results show that the method is effective for the suppression of strong chaotic noise when the signal to interference ratio is low.

Simultaneously Suppressing Low-Frequency and Relaxation Oscillation Intensity Noise in a DBR Single-Frequency Phosphate Fiber Laser

Effective multiple optoelectronic feedback circuits for simultaneously suppressing low-frequency and relaxation oscillation intensity noise in a single-frequency phosphate fiber laser are demonstrated. The forward transfer function, which relates the laser output intensity to the pump modulations, is measured and analyzed. A custom two-path feedback system operating at different frequency bands is designed to adjust the pump current directly. The relative intensity noise is decreased by 20dB from 0.2 to 5kHz and over lOdB from 5 to lOkHz. The relaxation oscillation peak is suppressed by 22dB. In addition, a long term （24h） laser instability of less than 0.05% is achieved.

Behavioral and Physiological Responses of Sea Slug (Onchidium reevesii) to Low-Frequency Noise

A large amount of marine noise pollution from coastal industrial construction and the water transportation industry affects the growth and development of marine life,which is a big issue threatening marine organisms.However,most studies have focused on vertebrates,such as marine mammals and fishes,and little is known about the effects of noise on invertebrates.Therefore,the impacts of low-frequency noise(100,300,and 500 Hz)on behavioral and physiological responsesof the sea slug(Onchidium reevesii)were investigated.Under laboratory conditions,sea slugs were stimulated with low-frequency noise at 100,300,and 500 Hz for 1 h.Then,hemolymph enzyme activities(glucose,albumin,triglycerides,superoxide dismutase,catalase,and malondialdehyde)were measured,and mRNA expression of the hsp70 gene was detected in hemolymph and the nervous system by quantitative realtime polymerase chain reaction(qRT-PCR)analysis,while expression of the hsp70 protein was analyzed by immunohistochemistry.The results demonstrated that sea slugs were away from the stimulus source under the influence of low-frequency noise compared to the control group.Enzyme activities,as well as hsp70 gene mRNA and protein expression levels,were significantly higher in the noiseexposed groups than those in the control group.Overall,these changes indicate that low-frequency noise caused oxidative stress in sea slugs in vivo,and the oxidative damage gradually increased when the noise frequency was increased from 100 to 500 Hz.

Low-Frequency Noise in Gate Tunable Topological Insulator Nanowire Field Emission Transistor near the Dirac Point

Low-frequency flicker noise is usually associated with material defects or imperfection of fabrication procedure. Up to now, there is only very limited knowledge about flicker noise of the topological insulator, whose topologically protected conducting surface is theoretically immune to back scattering. To suppress the bulk conductivity we synthesize antimony doped Bi2Se3 nanowires and conduct transport measurements at cryogenic temperatures. The low-frequency current noise measurement shows that the noise amplitude at the high-drain current regime can be described by Hooge＇s empirical relationship, while the noise level is significantly lower than that predicted by Hooge＇s model near the Dirac point. Furthermore, different frequency responses of noise power spectrum density for specific drain currents at the low drain current regime indicate the complex origin of noise sources of topological insulator.

Influence of Total Ionizing Dose Irradiation on Low-Frequency Noise Responses in Partially Depleted SOI nMOSFETs

Total ionizing dose effect induced low frequency degradations in 130nm partially depleted silicon-on-insulator （SOI） technology are studied by ^60Co γ -ray irradiation. The experimental results show that the flicker noise at the front gate is not affected by the radiation since the radiation induced trapped charge in the thin gate oxide can be ignored. However, both the Lorenz spectrum noise, which is related to the linear kink effect （LKE） at the front gate, and the flicker noise at the back gate are sensitive to radiation. The radiation induced trapped charge in shallow trench isolation and the buried oxide can deplete the nearby body region and can activate the traps which reside in the depletion region. These traps act as a GR center and accelerate the consumption of the accumulated holes in the floating body. It results in the attenuation of the LKE and the increase of the Lorenz spectrum noise. Simultaneously, the radiation induced trapped charge in the buried oxide can directly lead to an enhanced flicker noise at the back gate. The trapped charge density in the buried oxide is extracted to increase from 2.21×10^18 eV^-1 cm^-3 to 3.59×10^18？eV^-1 cm^-3 after irradiation.

Low-Frequency Noise in Amorphous Indium Zinc Oxide Thin Film Transistors with Aluminum Oxide Gate Insulator

Low-frequency noise（LFN） in all operation regions of amorphous indium zinc oxide（a-IZO） thin film transistors（TFTs） with an aluminum oxide gate insulator is investigated. Based on the LFN measured results, we extract the distribution of localized states in the band gap and the spatial distribution of border traps in the gate dielectric,and study the dependence of measured noise on the characteristic temperature of localized states for a-IZO TFTs with Al2 O3 gate dielectric. Further study on the LFN measured results shows that the gate voltage dependent noise data closely obey the mobility fluctuation model, and the average Hooge＇s parameter is about 1.18×10^-3.Considering the relationship between the free carrier number and the field effect mobility, we simulate the LFN using the △N-△μ model, and the total trap density near the IZO/oxide interface is about 1.23×10^18 cm^-3eV^-1.

Modeling and Analysis of Low Frequency Noise in Ion-Field-Effect Transistors Sensors

Ions Sensitive Field Effect Transistors (ISFETs) are becoming the platform sensors for important chemical and biomedical applications. However, the accuracy of ISFET output measurement is greatly affected by the presences of low-frequency noise, drift and slow response of the device. This requires more safety in measured results and the tools of analysis. In this paper, we present fundamental limits on the sensitivity of ISFETs micro-sensors, arising from intrinsic and extrinsic noise sources. We developed an algorithm in MATLAB in order to model the frequency analysis of the 1/f noise in ISFET sensor using Hooge theory. We have shown that the 1/f noise of the ISFETs sensors is due to both the electrochemical system (pH solution) and the MOS component (canal size, insulator thickness). The temperature effect on the ISFET noise and the signal conditioning are also performed.

New Applications of the Noise Spectroscopy for Hydrogen Sensors

Peculiarities of the low-frequency noise spectroscopy of hydrogen gas sensors made on MgFeO4 n-type porous semiconductor covered by the palladium catalytic nanosize particles are investigated. Behavior of the low-frequency noise spectral density and its exponent value from sensitive layer thickness in the frequency range 2 - 300 Hz are analyzed. Sensitivity of the sensor calculated by the noise method is several tenth times higher as compared with the resistive method. It is shown that besides of the well-known applications, noise spectroscopy can be also used for definition of the unknown thickness of gas sensitive layer, for definition of the sensitive layer subsurface role in the formation of the low-frequency noises and for definition of the intensity of trapping-detrapping processes of the gas molecules.

具有双线性发生率的随机酗酒模型

利用随机微分方程定性分析的方法,研究了一类具有双线性发生率的随机酗酒模型。将接触率系数的随机扰动引入确定型酗酒模型,研究了随机酗酒模型正解的存在性及唯一性。通过计算白噪声强度,得到了酗酒群体D(t)消失的充分性条件。研究结果显示,当外部干扰足够大时,酗酒群体、正在戒酒者、永久戒酒者都将消失。

基于强跟踪滤波器的水中高频振荡放电参数分析

为探明水中放电高频振荡阶段参数及其变化特性,提出一种基于自适应噪声完备集合经验模态分解(CEEMDAN)和强跟踪滤波器的时变参数辨识方法。通过该方法分解水中放电实验平台采集的电压、电流信号得到不同频率特征的信号分量,对最适应原始波形的信号分量开展Hilbert变换并求得相应的瞬时幅值、频率,进而得到所需的电阻和电感。实验数据离散度分析结果表明,放电进程中参数变化具有随机性,故利用强跟踪滤波器进一步对实验数据进行辨识处理,可有效地降低随机放电造成的离散性,并获得具备普适性的电阻值和电感值。偏离度分析结果表明,辨识电阻与测量数据除在气泡崩塌阶段随机性过大外,前期偏离度集中在23.26%以下,降低了偏离度处于80%~110%内数据点的干扰,电感偏离度集中在2.35%以下。该方法能够有效地应用于水中高频振荡放电过程的时变参数处理研究中。

基于优化聚类的人工源电磁法数据信噪分离方法

为了降低强电磁干扰对人工源电磁法(Controlled Source Electromagnetic Method,CSEM)有效信号的影响,改善CSEM实测数据处理结果因人而异且效率低的不足,本文针对CSEM有效信号周期性特征提出了一种加权自适应带宽均值漂移聚类(Weighted Adaptive Bandwidth Mean-Shift Clustering,WAB-MSC)信噪分离方法.首先在传统均值漂移聚类(Mean-Shift Clustering,MSC)算法的基础上增加核函数,降低处理结果对带宽选择的敏感度,提高算法的稳健性;其次结合实测CSEM数据的分布特征提出了一种基于局部密度梯度的带宽估计方法,实现了自适应带宽选择;最后通过仿真数据与实测数据对本文方法进行了验证,结果表明:本文方法能有效消除强电磁干扰对CSEM数据的影响,最大程度保留受噪声影响较小或未受噪声影响的数据,提高数据信噪比,降低强干扰噪声对CSEM初始资料的影响程度,获得更为真实的地电响应模型,为后续数据处理提供保障.

基于背景噪声有效值概率分布区间的强震台站监测能力分析

本文以珠江三角洲地震监测和预警系统粤东密集台网的强震日常记录数据为基础,利用强震台站背景噪声有效值密度函数,研究强震动台站背景噪声频谱的统计规律,建立强震台站背景噪声有效值平均模型、最小模型以及噪声有效值概率分布区间,通过利用强震台站背景噪声有效值概率分布区间与区域地震事件的频率-加速度幅值分布曲线互比的强震台站监测能力分析方法,得到了不同台站每日背景噪声加速度有效值,并估算了强震台站记录不同震级区域地震事件的概率,来评价台站的监测能力。强震台站背景噪声有效值概率分布区间分析方法是背景噪声有效值概率密度分布分析的延伸和拓展,有助于工程地震学中频率域去噪低端截止频率的讨论。由于仪器自噪声和环境噪声的相互作用不同而导致台站的噪声下限不同,强震台站背景噪声最小模型可以作为该台最优监测能力的估计,是强震仪及观测环境的综合指标。

强噪声干扰下采煤机行星齿轮故障诊断方法

采煤机摇臂截割部行星齿轮的健康状态直接影响截割效率。针对采煤机截割煤岩过程中受多重冲击引起的强噪声干扰、齿轮结构复杂且传递路径多变导致故障特征难以提取等特点,提出了一种基于频谱平均降噪和相关谱的采煤机行星齿轮故障诊断方法。根据信号频谱分布特征及噪声随机特性,采用频谱平均降噪方法抑制噪声对信号频谱的干扰,获得信号降噪频谱。构建相关谱以建立少样本降噪频谱和多样本降噪频谱的内在联系,减少频谱平均降噪对样本数量的需求。采用一维卷积神经网络(1D CNN)建立相关谱与故障类别之间的精确映射关系,以相关谱为输入、故障类别为输出,实现行星齿轮故障分类识别。在DDS传动系统故障诊断实验台对基于频谱平均降噪和相关谱的采煤机行星齿轮故障诊断方法进行实验验证,结果表明该方法能够增强表征故障特征的关键频率,对正常、断齿、磨损、缺齿和裂纹5种行星齿轮健康状态信号的整体识别率达96%,在信噪比不低于15 dB时可有效、准确地实现齿轮故障诊断。

强噪声与非周期脉冲激励下单稳系统的随机共振及应用

随机共振是噪声背景下非线性系统对微弱特征信号的最优响应,能够对微弱特征信号进行增强。偏置单稳态系统相较于传统的双稳态系统,对非周期脉冲激励具有良好的共振特性。然而,非线性系统的参数影响系统的最优输出,对不同的非周期脉冲激励,系统难以自适应调节。针对上述问题,该研究强噪声与非周期脉冲激励下偏置单稳态自适应随机共振。首先,基于优化算法实现不同非周期脉冲激励下的自适应随机共振。然后,以强噪声背景下钢丝绳漏磁检测信号为应用对象,经偏置单稳态系统自适应随机共振输出后,以峰峰值作为损伤特征演化评价指标,评估不同微弱损伤特征间的差异。同时,应用偏置单稳态自适应随机共振法和自适应移位平均法对强噪声背景下钢丝绳漏磁信号进行对比分析,以峰峰值增益和信噪比增益为指标,结果表明偏置单稳态自适应随机共振法效果优于自适应移位平均法。最后,讨论了噪声强度对单稳态自适应随机共振的影响,发现偏置单稳态自适应随机共振具有较强的抗噪能力。

非平稳强噪声环境中的音频信号端点检测系统

为提高音频信号端点识别能力,设计一种非平稳强噪声环境中的音频信号端点检测系统。构建音频信号端点检测硬件单元,利用预处理单元对音频信号进行预加重、分帧以及加窗处理后,端点检测单元在提取处理音频信号的MFCC倒谱距离特征、频带方差特征的基础上,依据动态阈值估计策略确定恰当阈值;通过双特征参数双门限法来实现对音频信号起止点的确定以及语音帧和非语音帧的分离;利用包络确定延时单元,防止噪声段被错误识别为语音段,避免出现拖尾太长问题。实验结果表明,所设计系统可实现非平稳强噪声环境音频信号端点检测,检测误差满足设定要求。

强噪背景下基于改进匹配追踪算法的桥梁缆索缺陷识别

为降低噪声对磁致伸缩导波信号的干扰,实现强噪背景下的桥梁缆索缺陷识别,提出了一种基于改进匹配追踪算法的桥梁缆索缺陷识别方法。首先,采用构建非对称Gabor函数作为原子字典,将相邻残差比作为迭代终止条件,对强噪背景下的导波信号进行匹配追踪。然后,通过缺陷回波包络峰值时刻,对桥梁缆索缺陷进行了定位。最后,对采用不同降噪方法时的桥梁缆索缺陷定位误差进行了比较。结果表明:未添加噪声时,采用缺陷回波包络峰值时刻定位桥梁拉索缺陷,最大误差仅为0.28%。当缺陷回波的信噪比高于-5 dB时,采用本文方法进行降噪,均方差E_(MSE)几乎为0,信噪比E_(SNR)增加到7.56 dB以上。采用本文方法对含噪导波信号进行降噪,其降噪精度和缺陷定位精度均优于小波阈值降噪、小波-EMD降噪和传统匹配追踪降噪。当导波信号信噪比为-5 dB及以下时,本文方法的优越性更为显著。即使导波信号信噪比达到-10 dB,采用本文方法进行降噪处理,拉索缺陷定位误差仍能达到1.5%以内。可见所提出的方法可以有效降低强噪声对实测导波的干扰,提高桥梁缆索缺陷识别精度。

基于声阵列的电力设备强干扰噪声源识别系统设计

由于外界强噪声干扰导致电力设备不能正常运行,为此,基于声阵列设计了一种新的电力设备强干扰噪声源识别系统。采用SJI19210型采集器采集信号,通过SIK-99101型处理器拼接组合信号,利用SUIJNUHJ121型分析器内部的进场声全息分析模块完成噪声源分析。分别设定噪声分析程序和声阵列识别程序,利用声阵列的扫描因子确定噪声源,完成电力设备强干扰噪声源识别。实验结果表明,所设计系统对稳定波动噪声信号噪声源识别精度高于96.42%,对不稳定信号噪声源识别精度在95.25%以上,对相对稳定噪声识别精度为94.36%,具有极强的识别能力。

基于局部均值分解和归一化最小均方的宽频振荡检测方法

为精确采集和分析电力系统宽频振荡信号,提出基于改进局部均值分解与归一化最小均方算法相结合的宽频振荡检测新方法。首先利用归一化最小均方算法对宽频振荡信号进行降噪处理,进而采用改进局部均值分解算法提取该降噪信号的乘积函数;然后对上述乘积函数分量进行希尔伯特变换,求解信号瞬时频率的高频突变点,实现对振荡起止时刻的准确定位。仿真实验表明,本文所提方法能准确求解宽频振荡信号,且在强噪声下仍具有很高的精度。

强噪环境下分频段数字音频信号精细化采集研究

在强噪环境下,为了获取高质量、低失真度的数字音频信号,提出一种强噪环境下分频段数字音频信号精细化采集方法。通过麦克风设备获取音频信号,利用LM4550芯片对其作采样、编码等处理后生成数字音频信号,基于AC-97单元接收数字音频信号,利用频段分割器对其作频带分解,获得互不重叠子频段数字音频信号。采用多窗谱谱减法对其去噪,利用数据通信接口将其传输给LM4550芯片,在完成模拟信号转换后,通过耳机输出,实现数字音频信号精细化采集。实验结果表明,该方法处理后的各子频段数字音频信号有用信息得以完整保留,并提高了信号波形的规整度和规律性,强噪声环境下数字音频信号的PESQ指标达到4.08以上,最大失真度为3.74%。

一次冷涡背景下强对流过程中风廓线雷达的应用

该文利用南通市兴东国家站风廓线雷达提供的资料,通过统计方法分析2017年8月7日南通出现的一次强对流天气过程。结果表明,此次强对流天气发生在冷涡背景下,处在副高边缘,本地水汽条件较好。风廓线雷达在强对流发生前能够清晰地体现冷暖平流的分布,风向风速的变化,对强对流过程的预报预警有很好的指示意义。垂直速度和信噪比与对流发生趋势较为一致,能够较好反映对流的变化。大气折射率结构常数能够很好地反映强对流的发生和结束。垂直风切变在强对流发生前60 min出现明显增大。