Spectral preconditioning of Krylov spaces: Combining PLS and PC regression

In regularized regression the vectors that lie in Krylov and eigen subspaces, formed in PLS and PC regressions respectively, provide useful low dimensional approximations for the LS regression coefficient vector. By preconditioning the LS normal equations we provide a framework in which to combine these methods, and so exploit both of their respective advantages. The link between the proposed method to orthogonal signal correction and to cyclic subspace regression is made. The performance of the proposed solution in reducing the dimension of the regression problem, and the shrinkage properties of the resulting coefficient vector, are both examined.     

Inferring (Biological) Signal Transduction Networks via Transitive Reductions of Directed Graphs

In this paper we consider the p-ary transitive reduction (TR _p ) problem where p>0 is an integer; for p=2 this problem arises in inferring a sparsest possible (biological) signal transduction network consistent with a set of experimental observations with a goal to minimize false positive inferences even if risking false negatives. Special cases of TR _p have been investigated before in different contexts; the best previous results are as follows:

Feature extraction by autoregressive spectral analysis using maximum likelihood estimation: internal carotid arterial Doppler signals

Abstract: In this study, Doppler signals recorded from the internal carotid artery (ICA) of 97 subjects were processed by personal computer using classical and model-based methods. Fast Fourier transform (classical method) and autoregressive (model-based method) methods were selected for processing the ICA Doppler signals. The parameters in the autoregressive method were found by using maximum likelihood estimation. The Doppler power spectra of the ICA Doppler signals were obtained by using these spectral analysis techniques. The variations in the shape of the Doppler spectra as a function of time were presented in the form of sonograms in order to obtain medical information. These Doppler spectra and sonograms were then used to compare the applied methods in terms of their frequency resolution and the effects in determination of stenosis and occlusion in the ICA. Reliable information on haemodynamic alterations in the ICA can be obtained by evaluation of these sonograms.     

BP神经网络算法预测及其在飞参数据分析中的应用

针对飞机喘振参数受随机因素影响的特点,提出了用人工神经网络中BP网络对飞机发动机喘振预测.通过对喘振数据及机组实际振动数据的预测结果检验,证明该神经网络预测有利于飞机发动机喘振状态的预测精度.     

基于MFC开发的振动信号监测与分析软件

利用微震测量技术、数据采集技术与信号处理技术可以建立一套监测各种振动信号的系统,广泛应用于各种振动事件的监测与报警。该文介绍了该系统的软件的设计思路与实现的效果。采用VC++,基于MFC类库开发了一套振动信号监测与分析软件,实现数据实时采集、信号分析处理、振动事件判别报警、数据存储回放等功能。     

多路矩阵开关信号采集系统设计研究

在传统矩阵信号采集和传输系统中,主要是对单个矩阵信号的采集和传输,但随着科技的发展,多路矩阵开关在工业和军事中的应用越来越广泛,对多路矩阵信号的有效采集和传输成为亟待解决的问题。本系统就是针对这个问题．在单个矩阵开关信号采集和传输的基础上,利用信号采集和传输的有关原理,采用串行通信技术和单片机控制技术实现了对多路矩阵信号的有效采集和传输。     

Gbps串行链路信号完整性分析与设计

本文对影响Gbps串行链路信号完整性(SI)的主要原因进行了详细分析,提出了一系列改善信号完整性的解决方法和思想。实际设计了实验背板,测试结果验证了方法的有效性。     

高温环境下测试信号传输的稳定性分析

针对测试过程中传输线受高温影响导致信号传输产生一定的不确定性的问题,提出了热电耦合的方法来研究导体的温度演变过程,计算温度变化影响下的电信号稳定性传输,并建立误差公式估算输入与输出电信号之间的关系。采用有限元方法建立了分析模型,讨论了外部环境与传输线的对流换热和通过电流时产生的焦耳热对导体产生的共同作用,以及影响电信号的稳定性传输的主要因素。此分析方法为提高高温环境下的结构测试的准确性提供了依据,对实际工程具有一定的指导意义。     

前置式磁控电弧传感器焊缝自动跟踪系统

针对目前机械式电弧传感器普遍存在的问题,将磁场控制电弧技术应用于焊缝跟踪,设计了磁控电弧传感器和一种双十字滑块的结构系统,对采样信号采用了RCπ型滤波和巴特沃思滤波器进行双级滤波,提出了有限区间去极值离散积分比较法来提取实际焊缝坡口的偏差信息。焊缝跟踪试验验证了该系统的有效性。     

光纤光栅传感器在结构健康监测中的应用

详细阐述光纤光栅传感器的结构及布拉格光纤光栅传感器的工作原理。重点介绍结构健康监测系统构成、光纤光栅传感器系统的信号处理、安装等方面问题;展望光纤光栅传感器在结构健康监测领域中的前景。