一种时频域联合捕捉主动声纳信号的方法

介绍了一种可应用于被动声纳的时频域联合捕捉主动声纳信号的方法及其工作流程。仿真相同噪声环境下使用该方法的发现距离与主动声纳探测距离,仿真结果表明使用该方法的发现距离远超过主动声纳探测距离,使用该方法可实现对目标的远程发现。     

基于虚拟仪器技术的信号测量分析仪的设计

针对传统仪器功能单一、传统编程语言的不足,采用计算机多线程技术、虚拟仪器技术等,根据信号自身的特点．结合信号处理方法,利用LabVIEW软件设计了虚拟信号测量分析仪。该分析仪可以对信号进行仿真、采集、多种时域参数的测量、小波降噪和频谱分析等功能,还可以实现波形的存储、回放。另外。该系统具有界面友好、扩展性强的优点,设计者可以通过软件改变系统功能,使用方便直观。经实践证明本软件达到良好的效果,可以进行推广。     

Turbo spin-echo sequences in magnetic resonance imaging of the brain: Physics and applications

Fast SE imaging provides considerable measure time reduction, high signal-to-noise ratios as well as similar contrast behavior compared to conventional SE sequences. Besides TR and TE_eff, echo train length (ETL), interecho time , and-space trajectory determine image contrast and image quality in fast SE sequences. True proton density contrast (CSF hypointense) and not too strong T2 contrast are essential requirements in routine brain MRI. A Turbo SE sequence with very short echo train length (ETL=3), short TE_eff and short interecho time (17 ms), and TR=2000 ms was selected for proton density contrast; a Turbo SE sequence with ETL=7, TE_eff=90 ms, =22 ms, and TR=3250 ms was selected for T₂-weighted images. Using both single-echo Turbo SE sequences yielded 50% measure time reduction compared to the conventional SE technique. Conventional SE and optimized Turbo SE sequences were compared in 150 patients resulting in very similar signal and contrast behavior. Furthermore, reduced flow artifacts in proton density—and especially in T₂-weighted Turbo SE images—and better contrast of high-intensity lesions in proton density-weighted Turbo SE images were found. Slightly reduced edge sharpness—mainly in T₂-weighted Turbo SE images—did not reduce diagnostic reliability. Differences between conventional and Turbo SE images concerning image contrast and quality are explained regarding special features of fast SE technique.Address for correspondence: Institut für Röntgendiagnostik, Klinikum der Universität Regensburg, Franz-Josef-Strauß-Allee 11, 93042 Regensburg, Germany. Additional reprints of this chapter may be obtained from the Reprints Department, Chapman & Hall, One Venn Plaza, New York, NY 10119.     

基于对称双通道脑电信号的注意力检测

注意力不能集中是一种注意力障碍,该现象普遍存在于青少年中,这直接影响人们的学习和工作效率.传统的注意力检测方法大多依赖对表情、姿势等行为的观察,难以客观精准地反映注意力情况.随着生理检测技术的迅猛发展,基于脑电信号的注意力检测近年来受到极大的关注.然而,相关研究仍存在检测准确率不高的问题.本研究收集了155位大学生在注意力集中、注意力非集中和放松3种状态下的脑电信号,并基于信号的小波特征、微分熵特征及功率谱特征,采用多种机器学习方法对3种注意力状态进行了识别.结果表明,脑电信号的小波特征,微分熵特征及功率谱特征可以有效区分被试的注意力状态,且基于对称双通道特征的平均准确率为(80.84±3)%,其检测精度明显高于基于单通道特征的检测精度.     

Tariff reduction as a tool to increase the efficiency of electricity distributors: A case study in southern Brazil

The article aims to evaluate the consumer response to a reduction in the electricity tariffs as a hourly economic signal for the case of an electric utility in the state of Rio Grande do Sul, southern Brazil. Using Differences-in-differences method, the results were robust in showing that the change in the economic signal increased up to 81.01% the consumption at the time influenced by the change, improving the way in which the company's assets are used, in addition to reducing fuel oil consumption by users.     

Performance Analysis of Machine Learning Algorithms for Classifying Hand Motion-Based EEG Brain Signals

Brain-computer interfaces (BCIs) records brain activity using electroencephalogram (EEG) headsets in the form of EEG signals; these signals can be recorded, processed and classified into different hand movements, which can be used to control other IoT devices. Classification of hand movements will be one step closer to applying these algorithms in real-life situations using EEG headsets. This paper uses different feature extraction techniques and sophisticated machine learning algorithms to classify hand movements from EEG brain signals to control prosthetic hands for amputated persons. To achieve good classification accuracy, denoising and feature extraction of EEG signals is a significant step. We saw a considerable increase in all the machine learning models when the moving average filter was applied to the raw EEG data. Feature extraction techniques like a fast fourier transform (FFT) and continuous wave transform (CWT) were used in this study; three types of features were extracted, i.e., FFT Features, CWT Coefficients and CWT scalogram images. We trained and compared different machine learning (ML) models like logistic regression, random forest, k-nearest neighbors (KNN), light gradient boosting machine (GBM) and XG boost on FFT and CWT features and deep learning (DL) models like VGG-16, DenseNet201 and ResNet50 trained on CWT scalogram images. XG Boost with FFT features gave the maximum accuracy of 88%.     

基于PXI接口多通道信源卡设计

多通道信号源是多路采集系统自检与测试系统的重要组成部分,为提高信号源的通用性,可靠性,可扩展性及小型化,结合PXI总线技术,设计出多通道信源卡;详细介绍了波形再生硬件模块,外部SRAM存储波形模块及满足设计要求边沿时间短的矩形波的软硬件设计,同时使用VHDL语言编写了数据通信协议模块,实现FPGA与计算机之间的正常通信。     

导弹数字舵机多通道信号转换及传输系统设计

针对全数字电动舵机无法直接使用传统的模拟信号及数据传输过程中丢帧、串帧、等待时间过长等问题,设计了一种基于DSP的多通道信号转换及传输系统,该系统采用片外AD及DA转换器实现信号转换,并针对传统通信算法存在的弊端,提出新的方法,实时配置FIFO中断等级,实现存在扰动情况下的无丢帧、无串帧通信,且执行时间37μs,提高了系统的稳定性、实时性。     

Computational Parametric Analysis of Cellular Solids with the Miura-Ori Metamaterial Geometry under Quasistatic Compressive Loads

Origami-based metamaterials have widespread application prospects in various industries including aerospace, automotive, flexible electronics, and civil engineering structures. Among the wide range of origami patterns, the fourfold tessellation known as Miura-ori is of particular attraction to engineers and designers. More specifically, researchers have proposed different 3D structures and metamaterials based on the geometric characteristics of this classic origami pattern. Herein, a computational modeling approach for the design and evaluation of 3D cellular solids with the Miura-ori metamaterial geometry which can be of zero or nonzero thicknesses is presented. To this end, first, a range of design alternatives generated based on a numerical parametric model is designed. Next, their mechanical properties and failure behavior under quasistatic axial compressive loads along three perpendicular directions are analyzed. Then, the effects of various geometric parameters on their energy absorption behavior under compression in the most appropriate direction are investigated. The findings of this study provide a basis for future experimental investigations and the potential application of such cellular solids for energy-absorbing purposes.     

尖端导体电晕放电试验研究

电晕放电是高压电力工程及航空航天领域研究的重点及难点问题;为研究尖端导体电晕放电的辐射特点,设计了电晕放电试验模拟系统;利用测试系统及天线在微波暗室内进行了不同测试距离、不同放电电压及不同尖端导体长度条件下的试验;通过对试验数据的分析可知,电晕放电辐射信号呈衰减振荡模式;电晕放电脉冲重复率随着充电电压的增大而增加;天线接收的辐射信号能量与测试距离成反比;随着充电电压的增加,信号辐射功率呈增加趋势;试验研究结果为输变电工程、航空航天装备的电磁环境分析提供参考。