盲分离技术识别发动机的噪声源

以柴油机为研究对象,对盲分离技术识别发动机噪声源进行了研究.用测得的混叠信号,盲分离技术能分离出各个噪声源,从而识别出噪声源.对比其他办法,该办法测试简单、测试仪器少、试验环境的条件要求低.用试验验证了新办法识别噪声源的有效性.     

Aggregation and the Nature of Price Expectations

Market liquidity requires differences of opinion among traders, but market behavior is often modeled using just one representative agent. This paper aggregates trading activity across many traders, at least one of which has rational expectations. Equilibrium price expectations depend on individual risk preferences and the expectations of all traders. Results indicate that positive feedback traders comprise a statistically significant minority of traders that has grown with the prevalence of commodity pools.     

A machine-learning method for improving crash injury severity analysis: a case study of work zone crashes in Cairo,Egypt

Abstract

The quality of vehicular collision data is crucial for studying the relationship between injury severity and collision factors. Misclassified injury severity data in the crash dataset, however, may cause inaccurate parameter estimates and consequently lead to biased conclusions and poorly designed countermeasures. This is particularly true for imbalanced data where the number of samples in one class far outnumber the other. To improve the classification performance of the injury severity, the paper presents a robust noise filtering technique to deal with the mislabels in the imbalanced crash dataset using the advanced machine learning algorithms. We examine the state-of-the-art filtering algorithms, including Iterative Noise Filtering based on the Fusion of Classifiers (INFFC), Iterative Partitioning Filter (IPF), and Saturation Filter (SatF). In the case study of Cairo (Egypt), the empirical results show that: (1) the mislabels in crash data significantly influence the injury severity predictions, and (2) the proposed M-IPF filter outperforms its counterparts in terms of the effectiveness and efficiency in eliminating the mislabels in crash data. The test results demonstrate the efficacy of the M-IPF in handling the data noise and mitigating the impacts thereof.     

高速铁路在农村地区环境问题的防治对策

文章就高速铁路在农村的几个常见的环境问题作了探讨并提出防治对策。文章对噪声污染、振动污染、大气污染等环境污染的原因做了简要分析之后,并对其进行了农村地区的防治对策的说明,希望对我国高速铁路在农村地区的环境问题的防治带来借鉴作用。     

谈高低频电路接地

在电子线路中,合理的接地方式能够有效抑制噪声和提高抗干扰能力。文章分析了电子线路中产生噪声干扰的一些原因,并讨论了一点接地及多点接地等接地方式消除噪声的方法。     

基于邻域信息的噪声图像的恢复

噪声图像的恢复是影响图像信息提取的一个重要因素。主要针对现存的噪声图像恢复算法在消除细线及椒盐噪声方面的困难,基于待检像素的邻域信息提出了一种针对细线和椒盐噪声感染的图像的恢复算法。实验结果表明,文中所提算法不仅具有很好的抑制细线及椒盐噪声的效果,而且有效地保存了图像的细节与结构信息,同时对其它的噪声也有一定的抑制作用。     

Investor Sentiment and Stock Returns: Evidence from Turkey

This paper investigates the relation between investor sentiment and stock returns on the Istanbul Stock Exchange, employing vector autoregressive (VAR) analysis and Granger causality tests. The sample period extends from July 1997 to June 2005. In the VAR models, stock portfolio returns and investor sentiment proxies are used as endogenous variables. Two dummy variables accounting for natural and economic crises are used as exogenous variables. The analysis results suggest that, excepting shares of equity issues in aggregate issues, stock portfolio returns seem to affect all investor sentiment proxies, namely closed-end fund discount, mutual fund flows, odd-lot sales-to-purchases ratio, and repo holdings of mutual funds. Investor sentiment does not appear to forecast future stock returns; only the turnover ratio of the stock market seems to have forecasting potential.     

房地产市场噪声交易行为分析——基于进化博弈理论的视角

噪声交易是房地产市场长期存在的一种现象,理性交易者与噪声交易者也长期并存于房地产市场。本文运用进化博弈理论研究房地产市场噪声交易者行为,分析噪声交易行为的复制动态,得到了理性投资者不可能利用投机行为把噪声交易者逐出市场的结论,同时给出了当博弈达到稳定均衡时选择理性交易策略和噪声交易策略的比例。     

股改前后中国股市噪声比较分析

以方差比检验(Variance-ratio test,VRT)为基础,构造一个噪声成分检验指标(Noise composition test,NCT),并以此做纵向分析,考察中国股票市场在股改前和股改后的噪声成分;同时,以40支近似全流通的股票和整个大盘做横向比较,得出的结论是:股权分置是噪声的重要来源,而股权分置改革和全流通有效地抑制了非理性因素和噪声。