一种基于MUSIC算法的涡街信号处理方法

针对涡街流量计易受管道振动和流场扰动引起噪声干扰的问题,提出了一种基于MUSIC算法的涡街信号处理方法.介绍了涡街流量计的测量原理,建立了噪声环境下的涡街信号模型,并阐述了MUSIC算法的基本原理,在此基础上,分别对多种噪声环境下的涡街信号进行仿真研究.仿真结果表明:所提的涡街信号处理方法能有效地抑制噪声,高精度地分辨频率点,对改善涡街流量计的性能有良好的效果.     

基于阵列扩展的宽带DOA估计算法

导向矢量的频率不一致性不利于宽带信号的DOA估计。为此,首先提出宽带直接空间谱估计算法,但是其限制条件过于苛刻;然后利用宽带信号的时延性质对阵列进行扩展,提出一种新的宽带DOA估计算法,新算法不需要DOA预估计;最后分析了梳妆谱和连续谱两种情形下如何使用新算法的问题。仿真实验结果表明,在信噪比较高的条件下,与传统算法相比,新算法的估计成功率更高,估计误差更小。     

复形态双向联想记忆网络及其性能分析

基于复数环(C,∨,∧,+)提出了复形态双向联想记忆网络模型,给出了神经网络实现双向完全联想记忆的条件,并分析了自联想的存储能力、稳定性和收敛性及神经网络的抗噪声能力.当复数虚部取零时即为实数,实数域形态双向联想记忆网络就是复数域形态双向联想记忆网络的特例.最后通过仿真实验验证复形态双向联想记忆网络的有效性.     

一种基于EEMD的新型谐波误差分析策略

针对电力系统中严重的谐波干扰问题,为提高其运行的安全有效性,去除谐波干扰并提高系统稳定性能成为研究热点。电网中常存在频率强烈波动或者白噪声强烈干扰的现象,虽说三谱线插值的FFT算法(基于Kaiser窗)的抗干扰能力很强,谐波参数估计也可以有较高的精准度,但是远不及使其与平均经验模态的总体水平来分解谐波的检测算法(EEMD)与直线度误差分析相结合。应用直线度误差来分析信号的谐波成分,有机结合了三谱线插值的FFT(基于Kaiser窗的)谐波检测分析法。通过对整体谐波分量的在线监测,不仅能够提高稳态信号的检测精度,还能提高系统的动态性能。本分析策略大限度地提高了计算精度以及系统稳定性。通过仿真分析得知,所述方法可以使系统具有较强的抑制频谱泄露能力,并能够显著降低栅栏效应的发生概率,进而使电力谐波信号的幅值误差、初相位误差和频率误差分别低于0.004 1%、0.002 4%和0.003 9%。     

认知无线电网络中安全的协作频谱检测算法

在认知无线电网络中,当认知用户存在虚假感知信息SSDF时,协作频谱感知的性能会受到巨大影响。为了确保频谱感知的鲁棒性,提出了一种基于信誉度加权序贯频谱检测算法来识别恶意用户并减轻他们造成的影响。该算法通过使用认知用户的近期感知信息计算本地信誉度函数,再综合考虑其信誉值与感知过程中表现的稳定程度以消除恶意用户对主用户的传输效率带来的影响。仿真结果表明,在恶意攻击环境下,新算法优于现有典型协作频谱感知算法。     

Effects of frequency dimming electronic ballast on a high‐pressure mercury thallium iodide discharge

This study focuses on the behavior of a cylindrical metal halide discharge lamp powered by frequency‐controlled electronic ballast. Half‐bridge electronic ballast was designed and achieved.     

面向频谱大数据处理的机器学习方法

随着移动互联网与物联网的迅猛发展,个人无线设备的数 量呈现指数级增长,随之产生的海量频谱数据与日俱增,频谱大数据的存在已成事实。同时 ,频谱赤字也日益严峻。为提高频谱利用率,有效的频谱大数据处理显得十分重要。本文从 无线通信的角度,首先给出了频谱大数据的定义并分析了它的基本特征;然后总结了一些 对于频谱大数据分析与利用颇具前景的机器学习方法,如分布式和并行式学习、极速学习、 核学习、深度学习、强化学习、博弈学习和迁移学习;最后给出了几个开放性话题和研究 趋势。     

Mutual spectral residual approach for multifocus image fusion

Multifocus image fusion is the process of obtaining a single image from multiple partially focused images such that the newly formed image consists of the well-defined information extracted from each source image. This paper proposes the use of saliency of the source images based on Mutual Spectral Residual. Spectral Residual brings out the unique/salient features of an image in frequency domain. The idea of proposed mutual spectral residual is to emphasize the relative unique features of a source image with respect to the other source images. The relative unique features are utilized to form saliency maps for each source image. These saliency maps can clearly indicate the focused and defocused parts of an image. Based on the saliency maps obtained, the image fusion takes place in spatial domain. Visual inspection and quantitative evaluation of the fused images obtained by the proposed method, using different evaluation metrics, demonstrate its effectiveness over several existing image fusion methods.     

Authentication of the 31 species of toxic and potent Chinese materia medica by microscopic technique assisted by ICP-MS analysis, part 4: four kinds of toxic and potent mineral arsenical CMMs

Toxic and Potent Chinese Materia Medica (T/PCMM) is a special and very important category of Chinese medicines. They have long been used in traditional medical practice and are being used more and more widely throughout the world in recent years. As there may be many fatal toxic effects caused by misusing or confusion of T/PCMM, their quality and safety control arouse increasing attention internationally. Researches on the accurate identification to ensure the safe use of T/PCMM are acquired; however, there are few reports on authentication. We are carrying out a series of studies on 31 T/PCMM originating from plants, animals, minerals, and secreta. In our previous studies, we proved that modern microscopic authentication is a simple, fast, effective, low cost, and less toxic method for identifying animal, seed, and flower T/PCMM. In the present study, we focused on the authentication of four kinds of mineral arsenicals, including orpiment (mainly containing As₂S₃), realgar (mainly containing As₄S₄), arsenolite, and arsenic trioxide (mainly containing As₂O₃). We examined the macroscopic and microscopic characteristics of the above minerals and found that they all can be easily identified and authenticated by using light microscopy coupled with polarized microscopy. Moreover, the authentication results for arsenolite and arsenic trioxide are confirmed by ICP‐MS analysis. We are sure that the morphological and microscopic characteristics indicated here are indispensable to establishing standards for these four mineral T/PCMMs. Microsc. Res. Tech. 74:1‐8, 2011. © 2010 Wiley‐Liss, Inc.     

频谱细化在电力谐波分析仪中的应用

论文提出一种基于二段式FFT频谱细化算法,利用了存贮空间中保存的前一次计算的数据,增加了实际计算的数据长度,在运算时间增加不多的情况下,提高了FFT的频率分辨率.并利用谐波分析仪上DSP芯片强大的数字信号处理能力对数据进行分析和处理.该算法作为谐波分析方法用于谐波分析仪中,能提高了谐波分析仪的精确度和快速性.