基于MMSE准则的MIMO多中继系统线性收发机设计

本文以放大转发MIMO多中继系统为研究对象,研究其联合线性收发机的优化设计问题,其基本思想是在中继的总发射功率约束下,最小化系统的均方误差(MSE).为降低系统复杂度,本文首先引入了乘积矩阵的奇异值分解,把收发机的设计简化为以奇异值向量和酉矩阵为优化变量的优化问题;接着利用变量替换并引入罚项,将简化后的问题转化成只有酉矩阵约束的优化问题.在此基础上,通过引入替换变量的欧氏梯度,设计了新的黎曼欧氏最陡下降算法,从而有效地处理酉矩阵约束.仿真结果表明,与传统的设计方法相比,本文提出的方案性能最优,最接近MSE下界.

加权系数平均法改进的小波域LMMSE信道估计算法

针对传统LMMSE算法需要知道信道特性的问题,提出了一种加权系数平均法改进的小波域LMMSE信道估计算法。运用离散小波变换对LS初始估计和预滤波处理后的信号实行阈值量化去噪处理,然后结合时域信道能量分布的稀疏性特征,利用加权系数平均法求出各子载波的频域响应,从而克服了传统LMMSE算法需要预先知晓信道统计特性的缺陷。对算法的BER和MSE性能进行实验仿真,结果表明:文中所提改进算法的信道估计整体性能显然会更优于LS、SVDLMMSE以及加权平均改进后的LMMSE算法。另外,在信噪比较低且信道统计特性未可知的状况下,文中算法要优于传统的LMMSE算法,并能够较好地降低噪声的影响,有效提升信道估计的精确度。

一种基于特征值的3D MMSE角度域波束赋形算法

将传统二维角度域波束赋形算法应用于三维多输入多输出(3D MIMO)场景时,会导致波形畸变、不稳定甚至失效。为此,在传统二维最小均方误差算法的基础上,提出一种改进的3D MMSE角度域波束赋形算法。在面阵信号模型中利用特征分解法对信号相关矩阵进行分解,去除与噪声相关的小特征值扰动因子,以此解决波形畸变与算法失效问题。仿真结果表明,该算法可实现3D角度域波束赋形,相对3D MVDR算法和ZF算法,其阵列输出均方误差较小,信干噪比较高。

基于差分隐私的直方图发布方法综述

在数字经济时代,数据发布是数据共享的重要环节。直方图数据发布是数据发布的常见方式,但它面临着隐私泄露的问题。为此,对基于差分隐私(DP)的直方图数据发布方法进行了研究。首先,介绍了DP和直方图的相关性质,以及近5年国内外针对静态数据集和流数据的直方图发布方法的研究,并讨论了静态数据下直方图分组数、分组方式、噪声误差和分组误差的均衡,以及隐私预算分配问题。其次,探讨了动态数据下数据采样、数据预测以及滑动窗口实现分组的问题;同时针对面向区间树结构的DP直方图发布方法,将原始数据与树结构进行转化,并讨论了树结构数据的加噪、基于树结构的优化、树结构的隐私预算的分配等;此外,还讨论了直方图发布数据的可用性和隐私性、查询范围和查询精度问题。最后,通过对相关算法进行对比分析,总结了各算法的优缺点,以及部分算法的定量分析比较及适用场景,展望了未来基于DP的直方图在不同数据场景中的研究方向。

基于KPCA-GA-BP模型的页岩气集输管道的内腐蚀速率预测

针对页岩气集输管道的内腐蚀,提出了一种基于KPCA-GA-BP组合模型的腐蚀速率预测算法。以某条页岩气集输管道的检测结果作为训练数据,运用反向传播(BP)神经网络建立预测模型,运用遗传算法(GA)优化了神经网络权值和阈值的初始值,运用核主成分分析法(KPCA)对数据进行了降维,在模型建立的过程中不断优化提升模型的预测精度,采用所建模型对另一条相邻管道进行预测并开挖验证。结果表明:选择TRAINGDM作为训练函数,隐含层节点为(8,1),遗传算法进化数为50,种群规模为100,交叉概率为0.3,变异概率为0.2,运用KPCA将数据从7维降为4维后,此模型的均方误差最低为0.12,当该模型用于相邻管道的预测时,均方误差为0.14。运用KPCAGA-BP模型,对页岩气集输管道内腐蚀速率进行预测具有一定的准确性,此模型可用于辅助指导现场内腐蚀直接评价等相关工作。

A Novel Approach for Developing a Linear Regression Model within Logistic Cluster Using Scikit-Learn

Due to the rapid development of logistic industry, transportation cost is also increasing, and finding trends in transportation activities will impact positively in investment in transportation infrastructure. There is limited literature and data-driven analysis about trends in transportation mode. This thesis delves into the operational challenges of vehicle performance management within logistics clusters, a critical aspect of efficient supply chain operations. It aims to address the issues faced by logistics organizations in optimizing their vehicle fleets’ performance, essential for seamless logistics operations. The study’s core design involves the development of a predictive logistics model based on regression, focused on forecasting, and evaluating vehicle performance in logistics clusters. It encompasses a comprehensive literature review, research methodology, data sources, variables, feature engineering, and model training and evaluation and F-test analysis was done to identify and verify the relationships between attributes and the target variable. The findings highlight the model’s efficacy, with a low mean squared error (MSE) value of 3.42, indicating its accuracy in predicting performance metrics. The high R-squared (R2) score of 0.921 emphasizes its ability to capture relationships between input characteristics and performance metrics. The model’s training and testing accuracy further attest to its reliability and generalization capabilities. In interpretation, this research underscores the practical significance of the findings. The regression-based model provides a practical solution for the logistics industry, enabling informed decisions regarding resource allocation, maintenance planning, and delivery route optimization. This contributes to enhanced overall logistics performance and customer service. By addressing performance gaps and embracing modern logistics technologies, the study supports the ongoing evolution of vehicle performance management in logistics clusters, fostering increased competitiveness and sustainability in the logistics sector.

全站仪自由设站法在基坑三维形变监测中的应用

针对传统基坑水平位移和竖向位移监测方法存在的作业烦琐、效率较低等弊端,采用徕卡TS15智能型全站仪自由设站法对其进行改善,实现基坑围护结构顶部水平和竖向位移的快速同步获取。通对自由设站法的原理及平差过程进行详细阐述,利用某建筑基坑项目进行实例应用,分析研究设站精度,并与传统监测方法获取的变形数据进行对比分析,结果表明:自由设站法设站点点位中误差在2mm左右,满足规范中点位中误差小于3mm的要求,与传统监测方法的差值相对较小,满足二等基坑监测规范精度要求;但当基坑监测等级为一级时,应采用测角精度为0.5"的高精度全站仪进行监测作业,确保监测数据满足规范精度要求。

Joint Transceiver Designs for Full-Duplex MIMO SWIPT Systems Based on MSE Criterion

For the simultaneous wireless information and power transfer(SWIPT), the full-duplex MIMO system can achieve simultaneous transmission of information and energy more efficiently than the half-duplex. Based on the mean-square-error(MSE) criterion, the optimization problem of joint transceiver design with transmitting power constraint and energy harvesting constraint is formulated. Next, by semidefinite relaxation(SDR) and randomization method, the SDRbased scheme is proposed. In order to reduce the complexity, the closed-form scheme is presented with some simplified measures. Robust beamforming is then studied considering the practical condition. The simulation results such as MSE versus signal-noise-ratio(SNR), MSE versus the iteration number, well prove the performance of the proposed schemes for the system model.

Performance of cumulant-based rank reduction estimator in presence of unexpected modeling errors

Compared with the rank reduction estimator(RARE) based on second-order statistics(called SOS-RARE), the RARE based on fourth-order cumulants(referred to as FOC-RARE) can handle more sources and restrain the negative impacts of the Gaussian colored noise. However, the unexpected modeling errors appearing in practice are known to significantly degrade the performance of the RARE. Therefore, the direction-of-arrival(DOA) estimation performance of the FOC-RARE is quantitatively derived. The explicit expression for direction-finding(DF) error is derived via the first-order perturbation analysis, and then the theoretical formula for the mean square error(MSE) is given. Simulation results demonstrate the validation of the theoretical analysis and reveal that the FOC-RARE is more robust to the unexpected modeling errors than the SOS-RARE.

基于均方误差修正的渗碳12CrNi3钢疲劳强度预测模型

为对渗碳12CrNi_(3)合金钢提供一种安全可靠的高周疲劳强度预测方法,本文利用高频疲劳测试机,在10^(4)~10^(8)循环周次内对渗碳12CrNi_(3)合金钢疲劳试样开展应力比为-1的高周疲劳实验。采用灰色估计法对渗碳12CrNi_(3)钢疲劳数据的威布尔W(α,β,γ)参数进行评估,并通过估算的威布尔参数,进一步确定渗碳12CrNi_(3)合金钢强度预测模型的参数。考虑应力-寿命关系,结合疲劳数据的威布尔分布规律,建立了失效概率为1%时的渗碳12CrNi_(3)合金钢高周疲劳强度预测模型。从预测疲劳强度安全可靠性出发,通过均方误差(MSE)方法对模型进行修正,并将修正后模型99%MSE下界线与渗碳12CrNi_(3)合金钢疲劳寿命P-S-N曲线(不同存活率P的S-N曲线)进行对比,研究发现12CrNi_(3)合金钢疲劳寿命数据点均位于模型99%MSE下界线内,预测结果很好。研究表明,在以渗碳12CrNi_(3)合金钢为材料,加载方式为拉压条件下的实际工程中,修正后模型99%MSE下界线可以更安全地作为构件可靠性设计的下界。

A Novel Adaptive Kalman Filter Based on Credibility Measure

It is quite often that the theoretic model used in the Kalman filtering may not be sufficiently accurate for practical applications,due to the fact that the covariances of noises are not exactly known.Our previous work reveals that in such scenario the filter calculated mean square errors(FMSE)and the true mean square errors(TMSE)become inconsistent,while FMSE and TMSE are consistent in the Kalman filter with accurate models.This can lead to low credibility of state estimation regardless of using Kalman filters or adaptive Kalman filters.Obviously,it is important to study the inconsistency issue since it is vital to understand the quantitative influence induced by the inaccurate models.Aiming at this,the concept of credibility is adopted to discuss the inconsistency problem in this paper.In order to formulate the degree of the credibility,a trust factor is constructed based on the FMSE and the TMSE.However,the trust factor can not be directly computed since the TMSE cannot be found for practical applications.Based on the definition of trust factor,the estimation of the trust factor is successfully modified to online estimation of the TMSE.More importantly,a necessary and sufficient condition is found,which turns out to be the basis for better design of Kalman filters with high performance.Accordingly,beyond trust factor estimation with Sage-Husa technique(TFE-SHT),three novel trust factor estimation methods,which are directly numerical solving method(TFE-DNS),the particle swarm optimization method(PSO)and expectation maximization-particle swarm optimization method(EM-PSO)are proposed.The analysis and simulation results both show that the proposed TFE-DNS is better than the TFE-SHT for the case of single unknown noise covariance.Meanwhile,the proposed EMPSO performs completely better than the EM and PSO on the estimation of the credibility degree and state when both noise covariances should be estimated online.

基于改进小波阈值函数的仪表图像去噪方法研究

传统小波去噪的软阈值函数和硬阈值函数在去噪过程中产生的恒定偏差与抖动会导致去噪后的图像存在模糊和伪吉布斯现象。基于此问题,该文提出了一种软硬兼顾的加权平均阈值函数,此阈值函数避免了传统阈值存在的“一刀切”问题,降低恒定偏差的同时具有连续性与渐进性。其次在改进传统阈值门限上,设计了一种随着分解层数增加而减少的自适应门限阈值,避免消除深层数的高频边缘信息。最后通过对含有不同高斯白噪声的仪表图片进行去噪,计算峰值信噪比与均方误差并对结果图像进行的客观分析评估,实验结果表明,该阈值函数方法相比于其他方法,去噪结果更为清晰,均方误差最小,峰值信噪比最大,去噪效果更佳。

不同标称精度全站仪变形监测数据精度对比分析

全站仪作为测绘仪器的典型代表,在变形监测领域中发挥着重要作用。本文以Trimble S9和南方NTS两种不同标称精度的全站仪为研究对象,分别对同一建筑物进行水平位移变形监测,对比两种全站仪监测成果的平均观测误差和点位中误差,并分别以两种全站仪的监测数据为基础建立预测模型,结果表明:Trimble S9全站仪相较于南方NTS监测成果的平均观测误差和点位中误差均较小,且预测模型精度远优于南方NTS预测模型。现代化全站仪能够最大程度降低观测误差,具有相对更高的测量精度,同时可进行二次开发利用,在常规监测和自动化监测领域均具有较高的适用性。

基于深度学习的图像风格迁移方法研究

为了快速实现图像风格迁移效果,提出基于深度学习的图像风格迁移方法。先将预处理目标内容图像和风格图像输入预训练VGG-19网络进行特征提取,再对特征损失系数进行设置,进而引入权重因子和平衡损失系数的最小二乘惩罚函数以加权求和方式获取总损失系数,最后依据梯度下降迭代方法进行图像重建,实现图像风格迁移效果。实验采用峰值信噪比(PSNR)和均方误差(MSE)来评价风格迁移图像的性能。结果显示,整体取得了很好的图像风格迁移效果。

A Comparison of Four Methods of Estimating the Scale Parameter for the Exponential Distribution

In this paper, the estimators of the scale parameter of the exponential distribution obtained by applying four methods, using complete data, are critically examined and compared. These methods are the Maximum Likelihood Estimator (MLE), the Square-Error Loss Function (BSE), the Entropy Loss Function (BEN) and the Composite LINEX Loss Function (BCL). The performance of these four methods was compared based on three criteria: the Mean Square Error (MSE), the Akaike Information Criterion (AIC), and the Bayesian Information Criterion (BIC). Using Monte Carlo simulation based on relevant samples, the comparisons in this study suggest that the Bayesian method is better than the maximum likelihood estimator with respect to the estimation of the parameter that offers the smallest values of MSE, AIC, and BIC. Confidence intervals were then assessed to test the performance of the methods by comparing the 95% CI and average lengths (AL) for all estimation methods, showing that the Bayesian methods still offer the best performance in terms of generating the smallest ALs.

分层先验总体中总体总量的经验贝叶斯预测

对具有分层逆伽马先验总体中总体总量的经验贝叶斯预测进行研究。首先,提出一种新方法得到总体总量的贝叶斯预测,并在此基础上获得总体总量的经验贝叶斯预测。其次,分情形探讨了经验贝叶斯预测的性质,结果表明它是渐近最优的,并在预测均方误差意义下优于最佳线性无偏预测。最后,通过模拟研究论证了论文的主要结论。

Interval Type-2 Fuzzy Model for Intelligent Fire Intensity Detection Algorithm with Decision Making in Low-Power Devices

Local markets in East Africa have been destroyed by raging fires,leading to the loss of life and property in the nearby communities.Electrical circuits,arson,and neglected charcoal stoves are the major causes of these fires.Previous methods,i.e.,satellites,are expensive to maintain and cause unnecessary delays.Also,unit-smoke detectors are highly prone to false alerts.In this paper,an Interval Type-2 TSK fuzzy model for an intelligent lightweight fire intensity detection algorithm with decision-making in low-power devices is proposed using a sparse inference rules approach.A free open–source MATLAB/Simulink fuzzy toolbox integrated into MATLAB 2018a is used to investigate the performance of the Interval Type-2 fuzzy model.Two crisp input parameters,namely:FIT and FIG��are used.Results show that the Interval Type-2 model achieved an accuracy value of FIO�=98.2%,MAE=1.3010,MSE=1.6938 and RMSE=1.3015 using regression analysis.The study shall assist the firefighting personnel in fully understanding and mitigating the current level of fire danger.As a result,the proposed solution can be fully implemented in low-cost,low-power fire detection systems to monitor the state of fire with improved accuracy and reduced false alerts.Through informed decision-making in low-cost fire detection devices,early warning notifications can be provided to aid in the rapid evacuation of people,thereby improving fire safety surveillance,management,and protection for the market community.

时程分析中地震动记录的调幅方法研究

建筑结构时程分析应选取合适的地震波,进行调幅后再后续分析。《建筑抗震设计规范》规定应选取三组或者七组及以上地震动记录进行时程分析;美国ASCE7-16建议,在进行弹塑性时程分析时,至少选取11组地震动记录进行分析。目前常用的地震动调幅方法有地面峰值加速度(GPA)调幅法、有效峰值加速度(EPA)调幅法和均方误差(MSE)调幅法。本文采用上述三种调幅方法对某框架-核心筒超高层结构进行弹性时程分析,分析比较不同调幅方法下地震动平均反应谱与规范反应谱匹配度、地震动基底剪力与规范反应谱基底剪力的差异。结果表明采用MSE调幅方法选取的地震动的平均反应谱与规范反应谱在频谱特性上更加吻合,同时地震动的基底剪力也能满足国内规范的要求。

基于新阈值函数的小波阈值去噪算法

针对传统小波阈值函数在阈值处的不连续性、小波估计系数存在偏差等不足,导致去噪后的图像出现失真、产生吉布斯震荡等问题,提出了一种改进的阈值函数,与常用的硬阈值、软阈值以及已有改进的阈值函数相比,该函数不仅易于计算,而且具有优越的数学特性。为了验证该阈值函数的优越性,通过仿真实验对几种小波去噪方法的峰值信噪比(PSNR)与均方差(MSE)进行了对比。实验结果表明,此去噪方法无论是在视觉效果上,还是在均方差和信噪比性能分析上均优于常用的阈值函数。

室内可见光通信中的分数间隔均衡技术

研究了室内可见光通信系统分数间隔均衡技术,以降低码间干扰对该通信系统性能的影响。针对室内可见光通信系统的传输特点和信号调制特性,建立了室内可见光通信链路模型;在此基础上,提出了分数间隔均衡方法,并利用最小均方误差准则优化设计均衡器。最后,通过计算机仿真,对提出的分数间隔均衡方法进行了性能评估。实验结果表明,相同误码率条件下,T/2分数间隔均衡器比符号间隔均衡器的性能优1～2dB,能够更有效地抑制由信道多径效应等引起的码间干扰,提高信号传输的可靠性。