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.

An innovative detection method of high frequency BPSK signal with low signal-to-noise ratio

Based on chaotic oscillator system, this paper proposes a novel method on high frequency low signal- to-noise ratio BPSK（ Binary Phase Shift Keying） signal detection. Chaotic oscillator system is a typical non-lin- ear system which is sensitive to periodic signals and immune to noise at the same time. Those properties make it possible to detect low signal-to-noise ratio signals. The BPSK signal is a common signal type which is widely used in modern communication. Starting from the analysis of advantages of chaotic, os~.illator system and signal features of the BPSK signal, we put forward a unique method that can detect low signar-to-noise ratio BPSK sig- nals with high frequency. The simulation results show that the novel method can dclct.t low signal-to-noise ratio BPSK signals with frequency in an order of magnitude of l0s Hz, and the input Signal-to-Noise Ratio threshold can be -20 dB.

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.

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.

Influence of signal-to-noise ratio on accuracy of spectral analysis by near infrared spectroscopy

As one of the important indicators of spectrometer,signal-to-noise ratio(SNR)reflects the ability of spectrometer to detect weak signals.To investigate the influence of SNR on the prediction accuracy of spectral analysis,we first introduce the major factors affecting the spectral SNR.Taking green tea as an example,the influence of spectral SNR on the prediction accuracy of the origin identification model is analyzed by experiments.At the same time,the relationship between the spectral SNR and prediction accuracy of spectral analysis model is fitted.Based on this,the common methods for improving the spectral SNR are discussed.The results show that the accuracy of the prediction set model first decreases slowly,then decreases linearly,and finally tends to be flat as the spectral SNR decreases.Through calculation,in order to achieve the prediction accuracy of prediction model reaching 90%and 85%,the spectral SNR is required to be higher than 23.42 dB and 21.16 dB,respectively.The overall results provide certain parameters support for the development of new online analytical spectroscopic instruments,especially for the technical indicators of SNR.

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.

Calculation method of the signal-to-noise ratio attribute of seismic data based on structural orientation

At present,most signal-to-noise ratio(SNR)estimation methods can only calculate the global and not the local SNR of seismic data.This paper proposes a calculation method of a structure-oriented-based seismic SNR attribute.The purpose is to characterize the temporal and spatial variation of the seismic data SNR.First,the local slope parameters of the seismic events are calculated using a plane wave decomposition filter.Then,the singular value decomposition method is used to calculate the local seismic data SNR,thereby obtaining it in time and space.The proposed method overcomes the insufficiency of a conventional global SNR to characterize any local seismic data features and uses the SNR as an attribute of seismic data to more accurately describe the signal-noise energy distribution characteristics of seismic data in time and space.The results of a theoretical model test and real data processing show that the SNR attribute can be used not only for seismic data quality evaluation but also for analysis and evaluation of denoising methods.

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.

Defected Ground Structure Multiple Input-Output Antenna For Wireless Applications

In this paper,the investigation of a novel compact 2×2,2×1,and 1×1 Ultra-Wide Band(UWB)based Multiple-Input Multiple-Output(MIMO)antenna with Defected Ground Structure(DGS)is employed.The proposed Electromagnetic Radiation Structures(ERS)is composed of multiple radiating elements.These MIMO antennas are designed and analyzed with and without DGS.The feeding is introduced by a microstrip-fed line to significantly moderate the radiating structure’s overall size,which is 60×40×1 mm.The high directivity and divergence characteristics are attained by introducing the microstripfed lines perpendicular to each other.And the projected MIMO antenna structures are compared with others by using parameters like Return Loss(RL),Voltage Standing Wave Ratio(VSWR),Radiation Pattern(RP),radiation efficiency,and directivity.The same MIMO set-up is redesigned with DGS,and the resultant parameters are compared.Finally,the Multiple Input and Multiple Output Radiating Structures with and without DGS are compared for result considerations like RL,VSWR,RP,radiation efficiency,and directivity.This projected antenna displays an omnidirectional RP with moderate gain,which is highly recommended for human healthcare applications.By introducing the defected ground structure in bottom layer the lower cut-off frequencies of 2.3,4.5 and 6.0 GHz are achieved with few biological effects on radio propagation in human body communications.The proposed design covers numerous well-known wireless standards,along with dual-function DGS slots,and it can be easily integrated into Wireless Body Area Networks(WBAN)in medical applications.This WBAN links the autonomous nodes that may be situated either in the clothes,on-body or beneath the skin of a person.This system typically advances the complete human body and the inter-connected nodes through a wireless communication channel.

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.

基于Raptor编码的多输入多输出光通信系统设计

为了提高可见光通信(Visible Light Communication,VLC)系统的复用增益,本文提出一种基于多输入多输出(Multiple Input Multiple Output,MIMO)的固定比例像素化VLC系统。系统首先执行空间角度映射,使数据的传送可在角域中进行;同时利用Raptor编码方法来跟踪由于窗口截断而引起的数据信道特性变化;然后对于使用高速相机捕捉到的一系列时变图像,利用散景效应获得所有链路距离上的固定比例图像。实验利用液晶显示器和高速相机,对所提出的VLC系统进行了验证。与传统的像素化MIMO系统相比,本文所提出的系统在未对准朝向的情境下具有更高的鲁棒性,从而在多路复用场景有着广泛的应用前景。

基于三稳态随机共振的ZPW-2000移频信号检测方法研究

针对ZPW-2000移频信号谐波干扰检测技术在抑制噪声时,不可避免损害有用信号的问题,提出三稳态随机共振系统,将部分噪声能量向移频信号能量转化,减少移频信号能量损失。首先,将移频信号的中心频率从较高频段搬移到较低频段,着重研究移频信号的有用频段。选取尺度变化系数为1 000,保证输入信号在尺度变化的过程中满足数值计算的稳定性,使尺度变换后的小参数信号满足绝热近似理论。其次,使用混沌麻雀算法(chaos sparrow search optimization algorithm, CSSOA)优化三稳态随机共振系统,得到输出信噪比(signal-to-noise ratios, SNR)最大时的系统参数a、b、c以及γ。然后,将搬移至低频区段的移频信号输入至优化后的三稳态随机共振系统,实现信号降噪。最后,对降噪信号采用复调制快速傅里叶算法(zoom fast fourier transformation, ZFFT)实现低频信号的检测。仿真结果表明:对比三稳态随机共振系统处理前后移频信号频谱图,显示频域特征增强,在降噪的同时不损害移频信号的能量;以-5 dB为步长将噪声注入至移频信号时,输出信噪比至少可提升16.54 dB;降噪后的信号通过ZFFT算法解调能够完成ZPW-2000移频信号低频信号的检测。对比经验模态分解算法、小波阈值算法等算法处理不同信噪比的含噪移频信号,验证混沌麻雀算法优化的三稳态随机共振系统输出信噪比较大,降噪效果较好,具有良好的抗干扰能力。研究结果为实现在抑制噪声的同时减少移频信号能量损失提供参考。

阻垢剂在低温多效海水淡化装置中的工业化应用

目前我国低温多效海水淡化水处理药剂基本为国外公司垄断,价格昂贵。国产海水淡化阻垢缓蚀剂也正在突破瓶颈,质量、性能日渐成熟,但是缺乏统一、完善系统的方法验证,同时缺乏大型海水淡化工程考核验收平台,导致海水淡化水处理药剂价格居高不下。为打破国外垄断,提升我国海水淡化药剂自主创新能力和核心竞争力,并降低药剂使用成本,采用2.5万t/d低温多效海水淡化装置,开展了SD210阻垢剂在工业化试验装置中应用研究。试验结果表明:在为期2个月的试验期内,在SD210投加质量浓度为4~8 mg/L条件下,装置运行安全、平稳,无明显结垢和腐蚀现象;且海水淡化装置产品水水质优于《生活饮用水卫生标准》(GB 5749—2006)所规定的指标要求。综上,SD210阻垢性能良好,能满足低温多效海水淡化装置使用要求。

沿江典型区域杨树大径材人工林复合经营技术研究

本文对杨树大径材培育周期内的5个典型复合经营模式生长和经济效益进行分析,选择出适宜长江沿江典型区域种植的杨树大径材复合经营模式。结果表明:参试林农复合经营模式下杨树的胸径、树高、单位面积蓄积量分别比纯林增加15.31%(YM)~20.92%(YYD)、9.52%(YM)~11.31%(YY)、45.66%(YM)~61.38%(YYD)。采用间作模式的6年生杨树复合经营总收益均大于杨树纯林,杨树间作模式的总产值为杨树纯林的2.78(YM)~4.47倍(YYD)。采用多作物间作模式总收益及总产值明显高于单作物间作模式。其中套种6年杨树-油菜-黄豆(YYD)模式累计总收益(11 905元/667m^(2))最高,杨树-小麦-黄豆(YMD)累计总收益(11 599元/667m^(2))次之。5个模式下6年生杨树木材收益由高到低依次为:YYD(7 244元/667m^(2))>YMD(7 197元/667m^(2))>YY(7 106.5元/667m^(2))>YM(6 539.6元/667m^(2))>YC(4 408.48元/667 m^(2))。杨树-油菜-黄豆(YYD)是促进大径材杨树生长、材积和经济效益最高的优选模式。此研究旨在为长江沿江典型区域杨树的大径材培育和复合经营策略提供参考。

计及改进阶梯型碳交易和热电联产机组灵活输出的园区综合能源系统低碳调度

为了进一步降低园区综合能源系统(park-level integrated energy system,PIES)碳排放量,优化热电联产(combined heat and power,CHP)机组出力的灵活性,提出一种考虑改进阶梯型碳交易和CHP热电灵活输出的PIES低碳经济调度策略。首先,将遗传算法与模糊控制相结合,设计一种遗传模糊碳交易参数优化器,从而对现有阶梯型碳交易机制进行改进,实现该机制参数的自适应变化;其次,在传统CHP中加入卡琳娜(Kalina)循环与电锅炉(electricboiler,EB),构造CHP热电灵活输出模型,以同时满足电、热负荷的不同需求;然后,提出一种柔性指标——电、热输出占比率,进而计算出电、热输出占比率区间,以衡量CHP运行灵活性;最后,将改进阶梯型碳交易机制和CHP热电灵活输出模型协同优化,以系统运行成本和碳交易成本之和最小为目标,构建PIES低碳经济优化模型。算例分析表明,所提策略可有效降低经济成本和碳排放量,同时还可扩展CHP灵活输出调节范围,能够为PIES低碳经济调度提供参考。