Using Pearson’s System of Curves to Approximate the Distributions of the Difference between Two Correlated Estimates of Signal-to-Noise Ratios: The Cases of Bivariate Normal and Bivariate Lognormal Distributions

Background: The signal-to-noise ratio (SNR) is recognized as an index of measurements reproducibility. We derive the maximum likelihood estimators of SNR and discuss confidence interval construction on the difference between two correlated SNRs when the readings are from bivariate normal and bivariate lognormal distribution. We use the Pearsons system of curves to approximate the difference between the two estimates and use the bootstrap methods to validate the approximate distributions of the statistic of interest. Methods: The paper uses the delta method to find the first four central moments, and hence the skewness and kurtosis which are important in the determination of the parameters of the Pearsons distribution. Results: The approach is illustrated in two examples;one from veterinary microbiology and food safety data and the other on data from clinical medicine. We derived the four central moments of the target statistics, together with the bootstrap method to evaluate the parameters of Pearsons distribution. The fitted Pearsons curves of Types I and II were recommended based on the available data. The R-codes are also provided to be readily used by the readers.

Acquisition Practice of High Signal-to-Noise Ratio in YTB Block of Sichuan Basin

YTB block in Sichuan basin is a favorable area to exploit oil and gas in shallow tight rock. 3D seismic project of this zone has two characteristics. Firstly, it has high requirements for the tolerance rate of the construction process and the acquisition of high signal-to-noise ratio seismic data;Second, there are widely obstacles and noises that lead to difficult acquisition construction organization. In acquisition practice, high signal-to-noise ratio seismic data was obtained by reasonable design of construction scheme, optimization of excitation parameters, improvement of receiving conditions and optimization of obstacle crossing observation system. .

Effective DOA Estimation Under Low Signal-to-Noise Ratio Based on Multi-Source Information Meta Fusion

Efficiently performing high-resolution direction of arrival(DOA)estimation under low signal-to-noise ratio(SNR)conditions has always been a challenge task in the literatures.Obvi-ously,in order to address this problem,the key is how to mine or reveal as much DOA related in-formation as possible from the degraded array outputs.However,it is certain that there is no per-fect solution for low SNR DOA estimation designed in the way of winner-takes-all.Therefore,this paper proposes to explore in depth the complementary DOA related information that exists in spa-tial spectrums acquired by different basic DOA estimators.Specifically,these basic spatial spec-trums are employed as the input of multi-source information fusion model.And the multi-source in-formation fusion model is composed of three heterogeneous meta learning machines,namely neural networks(NN),support vector machine(SVM),and random forests(RF).The final meta-spec-trum can be obtained by performing a final decision-making method.Experimental results illus-trate that the proposed information fusion based DOA estimation method can really make full use of the complementary information in the spatial spectrums obtained by different basic DOA estim-ators.Even under low SNR conditions,promising DOA estimation performance can be achieved.

Signal-to-noise ratio of lensless ghost interference with thermal incoherent light

Factors influencing the signal-to-noise ratio （SNR） of lensless ghost interference with thermal incoherent light are investigated. Our result shows that the SNR of lensless ghost interference is related to the transverse length of the object, the position of the object in the imaging system and the transverse size of the light source. Furthermore, the effects of these factors on the SNR are discussed in detail by numerical simulations.

Noises and Signal-to-Noise Ratio of Nanosize EIS and ISFET Biosensors

The results of comparative theoretical analyzes of the behavior of internal low-frequency noises, signal-to-noise ratio and sensitivity to DNA molecules for EIS and ISFET based nanosize biosensors are presented. It is shown that EIS biosensor is more sensitive to the presence of DNA molecules in aqueous solution than ISFET sensor. Internal electrical noises level decreases with the increase of concentration of DNA molecules in aqueous solution. In the frequency range 10−3 - 103 Hz noises level for EIS sensor about in three orders is higher than for ISFET sensor. In the other hand, signal-to-noise ratio for capacitive EIS biosensor is much higher than for ISFET sensor.

Enhancement of signal-to-noise ratio of ultracold polar NaCs molecular spectra by phase locking detection

We report a method of high-sensitively detecting the weak signal in photoassociation （PA） spectra of ultracold NaCs molecules by phase sensitive-demodulated trap-loss spectra of Na atoms from a photomultiplier tube. We find that the signal-to-noise ratio （SNR） of the PA spectra is strongly dependent on the integration time and the sensitivity of the lock-in amplifier, and our results show reasonable agreement with the theoretical analyses of the SNR with the demodulation parameters. Meanwhile, we investigate the effect of the interaction time of the PA laser with the colliding Na-Cs atom pairs on the SNR of the PA spectra. The atom loss rate is dependent on both the PA-induced atom loss and the loading of the MOT. The high-sensitive detection of the excited ultracold NaCs molecules lays a solid foundation for further study of the formation and application of ultracold NaCs molecules.

Signal-to-noise ratio of Raman signal measured by multichannel detectors

Raman spectroscopy has been widely used to characterize the physical properties of two-dimensional materials(2DMs).The signal-to-noise ratio(SNR or S/N ratio)of Raman signal usually serves as an important indicator to evaluate the instrumental performance rather than Raman intensity itself.Multichannel detectors with outstanding sensitivity,rapid acquisition speed and low noise level have been widely equipped in Raman instruments for the measurement of Raman signal.In this mini-review,we first introduce the recent advances of Raman spectroscopy of 2DMs.Then we take the most commonly used CCD detector and IGA array detector as examples to overview the various noise sources in Raman measurements and analyze their potential influences on SNR of Raman signal in experiments.This overview can contribute to a better understanding on the SNR of Raman signal and the performance of multichannel detector for numerous researchers and instrumental design for industry,as well as offer practical strategies for improving spectral quality in routine measurement.

Signal-to-noise ratio comparison of angular signal radiography and phase stepping method

Grating-based x-ray phase contrast imaging has the potential to be applied in future medical applications as it is compatible with both laboratory and synchrotron source. However, information retrieval methods are important because acquisition speed, scanning mode, image quality, and radiation dose depend on them. Phase-stepping （PS） is a widely used method to retrieve information, while angular signal radiography （ASR） is a newly established method. In this manuscript, signal-to-noise ratios （SNRs） of ASR are compared with that of PS. Numerical experiments are performed to validate theoretical results. SNRs comparison shows that for refraction and scattering images ASR has higher SNR than PS method, while for absorption image both methods have same SNR. Therefore, our conclusions would have guideline in future preclinical and clinical applications.

Local Correlated Noise Improvement of Signal-to-Noise Ratio Gain in an Ensemble of Noisy Neuron

We theoretically investigate the collective response of an ensemble of leaky integrate-and-fire neuron units to a noisy periodic signal by including local spatially correlated noise. By using the linear response theory, we obtained the analytic expression of signal-to-noise ratio (SNR). Numerical simulation results show that the rms amplitude of internal noise can be increased up to?an optimal value where the output SNR reaches a maximum value. Due to the existence of the local spatially correlated noise in the units of the ensemble, the SNR gain of the collective ensemble response can exceed unity and can be optimized when the nearest-neighborhood correlation is negative. This nonlinear collective phenomenon of SNR gain amplification in an ensemble of leaky integrate-and-fire neuron units can be related to the array stochastic resonance (SR) phenomenon. Furthermore, we also show that the SNR gain can also be optimized by tuning the number of neuron units, frequency and?amplitude of the weak periodic signal. The present study illustrates the potential to utilize the local spatially correlation noise and the number of ensemble units for optimizing the collective response of the neuron to inputs, as well as a guidance in the design of information processing devices to weak signal detection.

Identification of Maximum Road Friction Coefficient and Optimal Slip Ratio Based on Road Type Recognition

The identification of maximum road friction coefficient and optimal slip ratio is crucial to vehicle dynamics and control.However,it is always not easy to identify the maximum road friction coefficient with high robustness and good adaptability to various vehicle operating conditions.The existing investigations on robust identification of maximum road friction coefficient are unsatisfactory.In this paper,an identification approach based on road type recognition is proposed for the robust identification of maximum road friction coefficient and optimal slip ratio.The instantaneous road friction coefficient is estimated through the recursive least square with a forgetting factor method based on the single wheel model,and the estimated road friction coefficient and slip ratio are grouped in a set of samples in a small time interval before the current time,which are updated with time progressing.The current road type is recognized by comparing the samples of the estimated road friction coefficient with the standard road friction coefficient of each typical road,and the minimum statistical error is used as the recognition principle to improve identification robustness.Once the road type is recognized,the maximum road friction coefficient and optimal slip ratio are determined.The numerical simulation tests are conducted on two typical road friction conditions（single-friction and joint-friction）by using CarSim software.The test results show that there is little identification error between the identified maximum road friction coefficient and the pre-set value in CarSim.The proposed identification method has good robustness performance to external disturbances and good adaptability to various vehicle operating conditions and road variations,and the identification results can be used for the adjustment of vehicle active safety control strategies.

Effect of consolidation ratios on maximum dynamic shear modulus of sands

The dynamic shear modulus (DSM) is the most basic soil parameter in earthquake or other dynamic loading conditions and can be obtained through testing in the field or in the laboratory. The effect of consolidation ratios on the maximum DSM for two types of sand is investigated by using resonant column tests. And, an increment formula to obtain the maximum DSM for cases of consolidation ratio κc>1 is presented. The results indicate that the maximum DSM rises rapidly when κc is near 1 and then slows down, which means that the power function of the consolidation ratio increment κc-1 can be used to describe the variation of the maximum DSM due to κc>1. The results also indicate that the increase in the maximum DSM due to κc>1 is significantly larger than that predicted by Hardin and Black's formula.

Numerical study on maximum rebound ratio in blasting wave propagation along radian direction normal to joints

In the process of 2-D compressional wave propagation in a rock mass with multiple parallel joints along the radian direction normal to the joints, the maximum possible wave amplitude corresponding to the points between the two adjacent joints in the joint set is controlled by superposition of the multiple transmitted and the reflected waves, measured by the maximum rebound ratio. Parametric studies on the maximum rebound ratio along the radian direction normal to the joints were performed in universal distinct element code. The results show that the maximum rebound ratio is influenced by three factors, i.e., the normalized normal stiffness of joints, the ratio of joint spacing to wavelength and the joint from which the wave rebounds. The relationship between the maximum rebound ratio and the influence factors is generalized into five charts. Those charts can be used as the prediction model for estimating the maximum rebound ratio.

Experimental study on prediction model for maximum rebound ratio

The proposed prediction model for estimating the maximum rebound ratio was applied to a field explosion test, Mandai test in Singapore. The estimated possible maximum peak particle velocities(PPVs) were compared with the field records. Three of the four available field-recorded PPVs lie exactly below the estimated possible maximum values as expected, while the fourth available field-recorded PPV lies close to and a bit higher than the estimated maximum possible PPV. The comparison results show that the predicted PPVs from the proposed prediction model for the maximum rebound ratio match the field-recorded PPVs better than those from two empirical formulae. The very good agreement between the estimated and field-recorded values validates the proposed prediction model for estimating PPV in a rock mass with a set of joints due to application of a two dimensional compressional wave at the boundary of a tunnel or a borehole.

Maximum Ratio Combining Precoding for Multi-Antenna Relay Systems

This paper addresses the design of practical communication strategies for multi-antenna amplify-and-forward and decode-and-forward relay systems. We show that simple linear techniques at the source and destination in conjunction with maximum ratio combining can provide an optimal transmission strategy in terms of received SNR without imposing a huge computational load over the relay node(s). Besides, the structures of precoding matrices are very similar at the source and relay nodes, which reduces the complexity as all nodes can play the role of source and relay nodes without changing their transmission structure. Numerical results show that the proposed transmission and reception techniques can improve the received SNR, and hence enhance the ergodic capacity.

Speech Separation Methodology for Hearing Aid

In the design of hearing aids(HA),the real-time speech-enhancement is done.The digital hearing aids should provide high signal-to-noise ratio,gain improvement and should eliminate feedback.In generic hearing aids the perfor-mance towards different frequencies varies and non uniform.Existing noise can-cellation and speech separation methods drops the voice magnitude under the noise environment.The performance of the HA for frequency response is non uni-form.Existing noise suppression methods reduce the required signal strength also.So,the performance of uniform sub band analysis is poor when hearing aid is con-cern.In this paper,a speech separation method using Non-negative Matrix Fac-torization(NMF)algorithm is proposed for wavelet decomposition.The Proposed non-uniformfilter-bank was validated by parameters like band power,Signal-to-noise ratio(SNR),Mean Square Error(MSE),Signal to Noise and Dis-tortion Ratio(SINAD),Spurious-free dynamic range(SFDR),error and time.The speech recordings before and after separation was evaluated for quality using objective speech quality measures International Telecommunication Union-Telecommunication standard ITU-T P.862.

垭口微地形下档内线路不均匀覆冰研究

明确垭口地形因子对垭口输电线路覆冰的影响规律,对山区输电线路的差异化防冰非常关键。该文基于水文分析中反地形理论提出山腰垭口,建立垭口风场数值模型,并通过风洞实验验证该模型。依据垭口风场分布,选定3类垭口线路的架设路径,得出垭口线路的风速区间。将初始状态下导线单次覆冰冰层厚度不得超过线径的7%作为覆冰步长取值依据,循环计算流场、粒子传输模型、热力学方程得出线路风速区间内导线的覆冰情况,进而得出垭口线路的冰荷载曲线,山腰、山脉、双山垭口线路冰荷载曲线在弧垂区分别出现了弯折、下行、下凹的走势。通过野外垭口线路自然覆冰实验,验证了覆冰计算的有效性,证实横跨垭口线路的不均匀覆冰性,不均匀覆冰规律与计算冰荷载曲线类似。计算不同地形因子组合下3类垭口的冰荷载曲线,并提出最大应力比概念,作为评判覆冰所引起线路事故可能性的标准,量化了不同垭口地形因子与线路最大应力比之间的关系。

星载GNSS-R检测太湖水华可行性分析

星载全球导航卫星系统反射信号(GNSS-R)属于被动遥感技术,具有数据重访周期高、全天时、全天候、信号源丰富等优势。基于此,研究星载GNSS-R检测太湖水华的可行性。星载GNSS-R可以有效检测反射面的粗糙程度,通过使用相干反射表征反射面的粗糙度,研究不同风速区间内相干反射与蓝藻水华的关系。利用2020年4—8月美国气旋全球导航卫星系统(CYGNSS)数据,计算CYGNSS镜面反射点的时延多普勒图(DDM)功率比。以“哨兵-3”卫星水色遥感仪器(OLCI)影像最大特征峰高度(MPH)算法反演出的太湖叶绿素浓度作为参照,与欧洲中期天气预报中心(ECMWF)的风速产品进行时空间线性匹配,分析发现,在1~2.5 m/s风速区间内,叶绿素浓度达到0.1 mg/L以上时,极易引起镜面反射点发生相干反射,且功率比与叶绿素浓度的相关系数为0.84,具有良好的相关性。实验结果证明了利用星载GNSS-R的功率比及相关特性实现太湖水华检测的可行性。

基于联合仿真的电励磁同步电机线性自抗扰控制

针对电励磁同步电机(EESM)在车用电机控制方向的研究,通过Maxwell设计EESM有限元模型,基于Simulink搭建电机控制系统模型。然后,根据凸极EESM的电机特性和电磁转矩分析,在控制系统中采用最大转矩电流比(MTPA)矢量控制方式在Simulink-Maxwell进行EESM控制系统的联合仿真验证。同时,控制系统电流环应用线性自抗扰控制(LADRC),基于电机已知参数在LADRC中设计模型辅助—扩张状态观测器(MA-LESO),以观测和消除系统扰动变量。仿真实验表明,采用MTPA矢量控制的电机在带载时转速波动降低,带载能力增强;在电流环中采用MA-LESO的LADRC控制器能使电机转速在稳态时波动更小,在带载时的抗干扰性能更强,电机运行过程相对稳定;电机负载转矩和定子电流在空载、负载时的波形更稳定,显著提升了电机运行性能。

冲击螺杆钻具结构设计与参数优化

为了高效钻进硬岩地层,将螺杆钻具的大扭矩与轴向冲击工具的高频低幅冲击特性相结合,研制了一种冲击螺杆钻具。在工具结构原理讨论的基础上,建立了轴向冲击短节的冲锤运动控制方程,分析了冲锤的运动特性,并以工具冲击功和最大能量利用率为评价指标,采用正交试验方法对主要工具结构参数进行了优化研究。研究结果表明:冲锤往复运动过程为加速度逐渐减小的非线性加速运动,节流喷嘴直径和冲锤运动行程是影响冲击功的主要因素,而冲锤质量、承压面积和腔体通孔面积是次要因素。节流喷嘴直径和冲锤承压面积是影响最大能量利用率的主要因素;而冲锤运动行程、冲锤质量和腔体通孔面积是次要因素。所得结论可为对冲击螺杆钻具的进一步优化设计和现场应用提供参考。