独立分量分析及其在通信信号处理中的应用

独立分量分析是一种基于高阶统计量的信号分析方法,近年来作为信号处理的强有力分析处理工具得到广泛关注和研究.文章介绍了ICA的原理,并仿真了ICA算法在语音信号盲分离中的应用.     

浅谈调控一体化监控信号的管理

本文结合作者在信号监控方面的工作实际,从信号规范,信号分工,信号显示及信号处理等方面详细介绍分析了调控一体化监控信号管理工作的要点,并提出了相关信号工作的一些具体方法和经验。     

发掘股票投资中的财务信号与估值信号——基于中粮地产（000031）的案例分析

本文将信息经济学的信号理论应用于股票投资决策行为,旨在发掘股票投资中的财务信号和估值信号,并基于中粮地产的个股案例,全面客观地进行股票投资价值分析,试图为投资者股票投资提供决策建议。     

基于各向异性全变分的电磁信号降噪方法

电磁信号降噪是电磁信号检测中的重要研究内容,当电磁信息泄漏时,所辐射出的电磁信号中含有大量的噪声,该噪声具有随机性,给信号的进一步分析与提取带来了困难.文章通过对不同方向上的信号一阶梯度进行加权处理,提出了一个基于各向异性全变分的电磁信号降噪模型,该模型充分挖掘信号中噪声的结构,在抑制噪声的同时能够保留电磁信号中的信息...     

1000MW超超临界机组主汽再热疏水系统设计研究

本文结合国内外1000MW等级超临界机组的设计经验,经分析论证,提出了电厂三大蒸汽管道疏水采用温差信号(蒸汽过热度)来代替负荷信号控制三大蒸汽管道疏水阀的启闭的方案,该方案不仅具有更好的安全可靠性,同时还实现了工程的节能减排。     

语音信号短时分析算法研究与实现

在通信领域中,语音信号的研究层出不穷,语音信号处理是以语音语言学和数字信号处理为基础而形成的一门涉及面很广的综合性学科,其中,短时分析给语音信号处理提供了有力的分析方法。本文研究了语音信号的分析方法,即短时能量与短时平均幅度分析、短时过零率分析、短时相关分析、短时傅里叶变换分析,并利用MATLAB对语音信号的短时分析进行了算法实现。     

基于MATLAB小波分析的奇异信号检测的研究

本文在对不同信号的奇异性检测方法进行比较的基础上,总结了基于Wavelet变换的理论,并结合两仿真实例对小波分析在奇异信号检测上的应用进行了分析。     

某智能弹药模拟信号源设计

模拟信号源用于仿真某智能弹药工作过程中按不同的时序产生的信号。以此信号源提供激励信号,对某智能弹药电参数测试系统进行校验和调试。首先对不同的信号特征进行了分析,然后根据分析的结果设计了模拟信号源的硬件电路和软件程序,并对硬件电路进行了仿真。结果表明本设计满足某智能弹药测试系统的试验需求。     

Elman神经网络在雷达信号检测中的研究应用

雷达目标信号检测是雷达研究设计中的重要环节。本文在分析了传统目标信号检测技术的基础上,利用人工神经网络具有非线性和动态特性的特点,提出了一种基于Elman神经网络的信号检测的仿真设计方法,最终得到自适应性较强的Elman信号检测网络,完成对雷达目标信号的检测。     

基于声卡的便携式数据采集与分析系统设计

文章利用声卡作为数据采集设备,用数据分析和处理功能非常强大的工程实用软件Labview作为软件开发平台,设计了一个低成本、高性能的数据采集与分析系统。实现了数据采集、信号分析(时域分析和频域分析)及信号发生等多种功能。     

The ECA-method for Identifying Sensitive Reactions within an IO Context

The paper introduces an alternative method to determine "sensitivity' within an input–output-context and makes the most sensitive connections visible in an overall graph. The method called ECA (Elasticity Coefficient Analysis) tries—like the Important Coefficient Analysis (ICA)—to derive structures from a certain property of the Leontief inverse. As the core of the method is elasticity—i.e. taking the relative reaction of the element bij of the inverse as a measure of response to a 1% change of the input coefficient aij—it describes the dynamic potential of certain sectors on possible changes of technical coefficients. In the second part of the paper, comparisons are made between the results of MFA (Minimal Flow Analysis), ICA and ECA upon using the same table for analysis. ICA and ECA to some extent show similarities but also some differences. Both contrast with MFA with respect to the very basis of the approach that enforces different interpretations of the results. Finally, some hypotheses on the differences and similarities are set up that could give a perspective for the further use of the different methods.     

A conditionally heteroskedastic independent factor model with an application to financial stock returns

We propose a new conditionally heteroskedastic factor model, the GICA-GARCH model, which combines independent component analysis (ICA) and multivariate GARCH (MGARCH) models. This model assumes that the data are generated by a set of underlying independent components (ICs) that capture the co-movements among the observations, which are assumed to be conditionally heteroskedastic. The GICA-GARCH model separates the estimation of the ICs from their fitting with a univariate ARMA-GARCH model. Here, we will use two ICA approaches to find the ICs: the first estimates the components, maximizing their non-Gaussianity, while the second exploits the temporal structure of the data. After estimating and identifying the common ICs, we fit a univariate GARCH model to each of them in order to estimate their univariate conditional variances. The GICA-GARCH model then provides a new framework for modelling the multivariate conditional heteroskedasticity in which we can explain and forecast the conditional covariances of the observations by modelling the univariate conditional variances of a few common ICs. We report some simulation experiments to show the ability of ICA to discover leading factors in a multivariate vector of financial data. Finally, we present an empirical application to the Madrid stock market, where we evaluate the forecasting performances of the GICA-GARCH and two additional factor GARCH models: the orthogonal GARCH and the conditionally uncorrelated components GARCH.     

国际档案著录系列标准述评

国际档案理事会迄今为止已经制定了4个关于档案著录的标准，分别从不同方面对档案著录工作予以指导。本文对这一系列著录标准作了一个简单的介绍和特点总结。     

Observing each other’s observations in a Bayesian coordination game

We study a Bayesian coordination game where agents receive private information on the game’s payoff structure. In addition, agents receive private signals that inform them of each other’s private information. We show, that once agents possess these different types of information, there exists a coordination game in the evaluation of this information. Even though the precisions of both signal types are exogenous, the precision with which agents forecast each other’s actions in equilibrium turns out to be endogenous. As a consequence, there exist multiple equilibria which differ with regard to the way that agents weight their private information to forecast each other’s actions.     

基于ICA的图像去噪技术研究

ICA(Independent Component Analysis)可以仅由简单的几个假设条件,还原出原始相互独立的分量。利用ICA这一特点可对与噪声数据相互独立的图像数据进行分离,达到图像去噪的目的。文章对有噪图像进行小波处理,构建一个虚拟通道作为一个输入,对原有噪图像和构建出的虚拟通道进行分离,可得到去噪图像。传统去噪方法与文中所用方法的处理结果进行了比较。     

信号与系统课程的实验教学思考

信号与系统的课程理论比较内容枯燥,而且理论性比较强。实践课程通过丰富的实验来进一步加深学生对课堂上所学内容的理解,能充分弥补课堂上这部分内容无法与学生互动的不足。实践证明:学生在本门课的学习过程中,边学习理论边进行实验达到了较好的效果。学生的学习兴趣提高了,考试及格率同样提高了。     

铁路信号电源绝缘不良分析和处理

信号电源绝缘不良需要从多方面综合分析研究,要通过这一现象去发现深层次的问题。本文重点讨论铁路信号电源绝缘的不良分析以及处理方法。     

齿轮箱故障诊断振动信号处理方法的应用

介绍了齿轮箱故障基本形式及振动信号特征,然后通过实例对齿轮传动装置典型故障进行了一些分析,并得到了一定的验证,为建立自动诊断和智能诊断系统打下了一定的基础。     

财务报告舞弊动因分析与警戒信号识别

舞弊风险的评价是注册会计师在财务报告审计中能否有效查出舞弊的关键环节。学术界对这个方面已作了大量的研究,发现舞弊警戒信号可以帮助注册会计师提高准确评价舞弊风险水平的能力。本文主要就财务报告中的舞弊动因与警戒信号等问题作深入探讨。