Log-normal湍流信道中超奈奎斯特传输系统的误码性能

超奈奎斯特传输理论与调制技术相结合,可有效提高系统的频谱效率。本文将超奈奎斯特理论引入大气激光通信系统,构建了一种适合于log-normal湍流信道的超奈奎斯特光传输系统,推导了QPSK调制方式下超奈奎斯特大气光传输系统平均误码率的表达式,利用蒙特卡洛仿真进一步分析了该系统的误码性能及频谱效率。结果表明:采用超奈奎斯特技术方案可以较大幅度提升大气光传输系统的频谱效率,当SNR为18 dB,S.I.为0.4时其频谱效率可以达到1.7 Baud/Hz,而未采用超奈奎斯特技术时只有1.56 Baud/Hz。另一方面,大气湍流对超奈奎斯特系统误码性能的影响较明显,当S.I.为0.4,BER为3.8×10^-3时,信噪比恶化了约1 dB。相对于频谱效率的提升,误码性能的恶化是能够接受的。因此,可以将FTN技术引入大气光传输系统来提高系统的频谱效率。

Poisson Log-normal回归模型的影响评价(英文)

本文利用EM算法研究了来自于Lognormal分布权重的混合Poisson模型,即Poisson Lognormal回归模型,从而利用基于完全数据似然函数的条件期望进行影响评价.基于数据删除模型和局部影响分析方法,分别得到了广义Cook距离、Q距离和三种不同扰动模型下的正则曲率度量等诊断统计量.

一种估算三参数log-normal分布参数的近似方法

三参数（ｌｏｇ－ｎｏｒｍａｌ）分布在可靠性工程中有广泛应用，但其分布参数的估计较为困难。为解决这一问题，本文将极大似然法引入其概率图。

Log-normal分布杂波背景下有序统计恒虚警检测器性能分析

该文证明了在形状参数已知的均匀对数-正态(Log-normal)杂波背景下有序统计恒虚警(OS-CFAR)检测器能保持恒虚警的特性,导出了该背景下OS-CFAR检测器对非起伏目标的检测性能表达式和平均判决阈值(ADT)表达式。最后用数值方法讨论了最佳序值的选取以及OS-CFAR检测器在取不同参考单元数时相对于理想CFAR的信杂比损失。

变环境不同阶段下Log-normal分布缺失数据的可靠性估计

本文研究了变环境不同阶段Log-normal分布下,观测数据中包含缺失数据的情形下的可靠性估计问题。通过EM算法估计参数以及可靠性,最后通过模拟研究验证了本文方法的可行性。

A new car-following model yielding log-normal type headways distributions

Modeling time headways between vehicles has attracted increasing interest in the traffic flow research field recently, because the corresponding statistics help to reveal the intrinsic interactions governing the vehicle dynamics. However, most previous micro-simulation models cannot yield the observed log-normal distributed headways. This paper designs a new car-following model inspired by the Galton board to reproduce the observed time-headway distributions as well as the complex traffic phenomena. The consistency between the empirical data and the simulation results indicates that this new car-following model provides a reasonable description of the car-following behaviours.

Efficient Mean Estimation in Log-normal Linear Models with First-order Correlated Errors

In this paper, we propose a log-normal linear model whose errors are first-order correlated, and suggest a two-stage method for the efficient estimation of the conditional mean of the response variable at the original scale. We obtain two estimators which minimize the asymptotic mean squared error （MM） and the asymptotic bias （MB）, respectively. Both the estimators are very easy to implement, and simulation studies show that they are perform better.

Linear Maximum Likelihood Regression Analysis for Untransformed Log-Normally Distributed Data

Medical research data are often skewed and heteroscedastic. It has therefore become practice to log-transform data in regression analysis, in order to stabilize the variance. Regression analysis on log-transformed data estimates the relative effect, whereas it is often the absolute effect of a predictor that is of interest. We propose a maximum likelihood (ML)-based approach to estimate a linear regression model on log-normal, heteroscedastic data. The new method was evaluated with a large simulation study. Log-normal observations were generated according to the simulation models and parameters were estimated using the new ML method, ordinary least-squares regression (LS) and weighed least-squares regression (WLS). All three methods produced unbiased estimates of parameters and expected response, and ML and WLS yielded smaller standard errors than LS. The approximate normality of the Wald statistic, used for tests of the ML estimates, in most situations produced correct type I error risk. Only ML and WLS produced correct confidence intervals for the estimated expected value. ML had the highest power for tests regarding β1.

Suppression of Log-Normal Distributed Weather Clutter Observed by an S-Band Radar

We have observed weather clutter containing targets (ships) using an S-band radar with a frequency 3.05 GHz, a beam width 1.8°, and a pulsewidth 0.5 μs. To investigate the weather clutter amplitude statistics, we introduce the Akaike Information Criterion (AIC). We have found that the weather clutter amplitudes obey the log-normal, Weibull, and log-Weibull distributions with the shape parameters of 0.308 to 0.470, 4.42 to 4.51, and 15.91 to 16.44, respectively, for small data within the beam width of an antenna. We have proposed the log-normal/CFAR circuit modified a Cell-Averaging (CA) LOG/CFAR circuit. It is found that weather clutter is suppressed with improvement of 51.58 dB by log-normal/CFAR. As a result, we have showed that weather clutter observed by S-band radar does not obey the Rayleigh distribution and our log-normal/CFAR circuit has an effect on suppression of clutter and detection of target, while conventional LOG/CFAR circuit does not. In addition, if our circuit can be realized, we will have an advantage economically.

Log-normal censored regression model detecting prognostic factors in gastric cancer:A study of 3018 cases

AIM:To investigate the efficiency of Cox proportional hazard model in detecting prognostic factors for gastric cancer.METHODS:We used the log-normal regression model to evaluate prognostic factors in gastric cancer and compared it with the Cox model.Three thousand and eighteen gastric cancer patients who received a gastrectomy between 1980 and 2004 were retrospectively evaluated.Clinic-pathological factors were included in a log-normal model as well as Cox model.The akaike information criterion (AIC) was employed to compare the efficiency of both models.Univariate analysis indicated that age at diagnosis,past history,cancer location,distant metastasis status,surgical curative degree,combined other organ resection,Borrmann type,Lauren's classification,pT stage,total dissected nodes and pN stage were prognostic factors in both log-normal and Cox models.RESULTS:In the final multivariate model,age at diagnosis,past history,surgical curative degree,Borrmann type,Lauren's classification,pT stage,and pN stage were significant prognostic factors in both log-normal and Cox models.However,cancer location,distant metastasis status,and histology types were found to be significant prognostic factors in log-normal results alone.According to AIC,the log-normal model performed better than the Cox proportional hazard model (AIC value:2534.72 vs 1693.56).CONCLUSION:It is suggested that the log-normal regression model can be a useful statistical model to evaluate prognostic factors instead of the Cox proportional hazard model.

Two indicators rule them all:Mean and standard deviation used to calculate other journal indicators based on log-normal distribution of citation counts

Two journal-level indicators,respectively the mean(mi)and the standard deviation(vi)are proposed to be the core indicators of each journal and we show that quite several other indicators can be calculated from those two core indicators,assuming that yearly citation counts of papers in each journal follow more or less a log-normal distribution.Those other journal-level indicators include journal index,journal one-by-one-sample comparison citation success index S_(j)^(i),journal multiple-sample K^(i)-K^(j) comparison success rate S_(j,k^(j)^(i,k^(i))),and minimum representative sizes k_(j)^(i) and k_(i)^(j),the average ranking of all papers in a journal in a set of journals(R^(t)).We find that those indicators are consistent with those calculated directly using the raw citation data({C^(i)=(c_(1)^(i),c_(2)^(j),...c_(N)^(i),■i})of journals.In addition to its theoretical significance,the ability to estimate other indicators from core indicators has practical implications.This feature enables individuals who lack access to raw citation count data to utilize other indicators by simply using core indicators,which are typically easily accessible.

Performance analysis of space-shift keying over negative-exponential and log-normal FSO channels

The average bit-error rate （ABER） performance of free-space optical （FSO） communication links is investigated for space-shift keying （SSK） over log-normal and negative-exponential atmospheric turbulence channels. SSK is compared with repetition codes and a single-input single-output system using multiple pulse amplitude mod- ulations. Simulation results show that the signal-to-noise ratio gain of SSK largely increases with greater spectral efficiencies and/or higher turbulence effects. A tight bound for ABER is derived based on an exact moment generation function （MGF） for negative-exponential channel and an approximate MGF for log-normal channel. Finally, extensive Monte Carlo simulations are run to validate the analytical analysis.

Performance Analysis of a DS-CDMA Cellular System with Effects of Soft Handoff in Log-Normal Shadowing Channels

Next generation wireless communication is based on a global system of fixed and wireless mobile services thatare transportable across different network back-bones,network service providers and network geographical boundaries.This paper presents an approach to investigate the effects of soft handover and perfect power control on the forward link ina DS-CDMA cellular system.Especially,the relationships between the size ofhandover zone and the capacity gain are e-valuated under the log-normal shadow channel.Then the optimization of maximum forward capacity is very necessary tobe done with the maximum size of soft handover zone to the various system characteristics.

数据驱动与有限元仿真融合的纱线断裂强力分析方法

为揭示机器人运动速度等参数对纱线性能的影响规律,考虑纱线夹持长度与拉伸速度对断裂强力分布的影响,分析了动态环境下环锭纺细纱断裂强力的分布特征。首先设计拉伸实验对环锭纺细纱性能进行分析,并构建了环锭纺短纤纱本构模型表征其强伸性能。其次建立有限元仿真模型模拟短纤纱的断裂过程,揭示了纤维间载荷传播的规律和纱体结构演化的4个阶段模型。最后对纱线强力数据的统计特征进行分析,建立了其分布参数模型。结果表明,分布检验与威布尔分布相比,对数正态分布的拟合误差最小,残差平方和为0.0006,进一步提高了动态环境下环锭纺细纱强力预测的可靠性。

闪电资料在成都地区闪电定位数据质量控制中的应用

成都平原属暖湿亚热带太平洋东南季风气候区,中小尺度天气系统十分活跃,雷电活动频繁,分析和应用地基闪电定位系统(advanced direction and time-of-arrival detecting system,ADTD)闪电监测资料须对闪电数据实施质量优选。利用成都地区2011—2020年间的闪电监测资料,分析得出成都地区小幅值闪电的时间分布特征。采用对数正态拟合分析方法得出成都地区闪电监测资料中小幅值地闪的干扰范围为绝对值≤3.10 kA,对数正态拟合检验表明剔除该部分闪电数据后拟合效果更佳。研究表明对数正态分析方法可以定量化确定成都地区小幅值闪电数据中的干扰区间,从而为该地区的闪电资料处理及应用提供了理论依据。

三维井筒套管柱居中度设计——以川渝油气田为例

套管居中度对固井质量存在较大影响,合理设计套管居中度将极大改善套管环空流场分布,提高环空顶替效率,确保水泥环质量,为后续钻进和储层改造奠定基础。通过对现有主流套管柱居中度计算模型的局限性分析,提出因三维井筒中套管柱所受重力和轴向载荷不位于单一平面内,将发生非平面挠曲变形,侧向受力和径向偏移受到井筒轨迹和浮力变化影响的观点。基于真实井眼轨迹的三维形态,考虑井筒管柱轴向拉力对主、副法向平面挠度以及浮力效应的影响,建立了三维套管单跨梁居中度数学模型,编制了套管柱居中度模拟分析计算模块。通过与实钻井居中度成像测井数据对比表明:①该计算模式模拟结果与IBC套后成像测井实测居中度数据的平均整体误差仅7.6%;②通过增大直井段扶正器外径、尾管段替入清水实现漂浮效应减弱套管柱径向偏移量、合理加密安置上部直井段刚性扶正器间距等优化措施,能够显著提升管柱整体居中度至70%以上并改善水泥环质量。该设计模式能够有效指导川渝油气田高压气区套管居中度设计,对于提高复杂井筒环空封固质量有重要意义。

基于最优k值k-means聚类分析的湖相沉积土层岩土参数分布研究

对岩土参数进行传统的k-means聚类分析时,因无法确定k值,而导致无法有效剔除误差数据。为得到岩土参数可靠取值范围,基于最优k值的k-means算法进行研究,通过量化样本内距离和聚类紧密性来确定聚类数目k值,避免了传统k值的随机选取。对粉土的三个基本物理力学指标:黏聚力c、内摩擦角φ、压缩模量E_(s)进行空间聚类分析。通过比较不同k值时的E_(E)值,确定最优k值为5。聚类完成后,原样本被划分为5类子样本。样本数量最多的一类为最优子样本,这类子样本与原样本分布一致,且数量偏离程度及变异性较小。对除最优类外的其他四类子样本进行分布检验,可知A-D检验法适用于小样本,而K-S检验法适用于大样本。根据偏度系数c值,调整合适的区间长度,进一步优化参数取值范围,并与工程实际采用值对比,检验方法的可行性。该分析方法实现由小样本代替大样本进行参数统计分析求取可靠的取值区间,简化计算,提高工作效率。

基于FA-LN-BiGRU的机械设备剩余寿命区间预测方法

针对数据驱动融合模型存在前后模型不匹配、关键信息丢失等问题,提出了一种端对端的预测方法,即基于特征注意力机制的对数正态分布和双向门控循环单元融合(feature attention-lognorm-bidirectional gated recurrent unit,简称FA-LN-BiGRU)的剩余寿命区间预测方法。首先,利用特征注意力机制从多维度、非线性和大规模的传感器信号中提取出关键特征向量;其次,采用BiGRU网络从前向和后向2个方向对注意力加权特征的时变特性进行建模学习,并通过最大似然估计损失函数来训练网络参数,获得网络隐含状态输出向量的概率分布;最后,计算出基于对数正态分布的概率密度函数,实现设备剩余寿命(remaining useful life,简称RUL)不确定性的衡量。分析结果表明,对于运行条件复杂和故障模式多变的多维监测数据,所提方法能够深入挖掘性能退化信息,有效提高机械设备剩余寿命点预测和区间预测的准确度和可靠性。

响应数据缺失下一般线性复合分位数光滑经验似然估计

由于分位数回归模型的损失函数不光滑,所得参数估计的效率不高,为提高参数估计的效率,首先提出复合分位数光滑经验对数似然比,包括完全数据复合分位数光滑经验对数似然比、加权复合分位数光滑经验对数似然比和插值复合分位数光滑经验对数似然比,并在一定条件下证明了它们都是服从渐近卡方分布的.其次,根据该似然比构造了回归参数的置信区间,并证明了复合分位数光滑经验似然估计量是渐近正态的.最后,通过数值模拟实验说明了所得估计的有效性.