上海股市对技术信号的价格反应模型

中国股市中众多的技术分析派投资者提供了研究技术分析信息对股价影响的典型样本,文章以趋同性投资行为的合理预期为假设前提,通过建立基于技术信号的股价反应自适应预期模型,对上海股市对技术信号的反应进行实证分析。结果表明,上海股市对技术信号的反应较为敏感,当技术趋势信号发生较大的变化时,对股票价格运行的影响较为强烈。考虑到实际交易费用,只有少数投资者依靠技术分析获得一定的超常收益,大多数投资者利用技术信号进行操作时要承担相当大的风险。     

AMW谱估计算法以及在信号识别中的应用

本文在对Burg格型算法谱线分裂原因分析、讨论的基础上,提出了一种短数据点时AMW算法,并对其性能进行了分析。讨论了这种AMW算法在信号识别中的应用,提出了一种基于AMW算法的信号检测方法。此外,还在附录中,给出了此算法稳定的证明。     

神经网络用于通信信号分类识别研究

介绍了将神经网络方法应用于通信信号的分选和识别的初步研究结果；选择了二值自适应共振（ＡＲＴ１）神经网络完成对输入信号的分类，确定输入信号类型是否已被网络存储，发现新出现的信号并标记；再采用多层前馈误差反向传播（ＢＰ）神经网络完成每一标记信号的识别，即识别该信号类型。比较了神经网络分类识别器和树形分类器的性能，并给出了计算机模拟结果。结果表明，基于神经网络的分类识别器的性能远优于传统技术分类器。     

A Basis Function Approach to Position Estimation Using Microwave Arrays

We consider the problem of estimating the bearing of a remote object given measurements on a particular type of non-scanning radar, namely a focal-plane array. Such a system focuses incoming radiation through a lens onto an array of detectors. The problem is to estimate the angular position of the radiation source given measurements on the array of detectors and knowledge of the properties of the lens. The training data are essentially noiseless, and an estimator is derived for noisy test conditions. An approach based on kernel basis functions is developed. The estimate of the basis function weights is achieved through a regularization or roughness penalty approach. Choosing the regularization parameter to be proportional to the inverse of the input signal-to-noise ratio leads to a minimum prediction error. Experimental results for a 12-element detector array support the theoretical predictions.     

An application of taguchi's methods reconsidered

Two aspects of Taguchi's methods for analyzing parameter design experiments that can be improved upon are considered. It is shown how using interaction graphs instead of marginal graphs, and how using the sample variance instead of a signal-to-noise ratio, can lead to product designs that are more robust to variation. The advantages of the alternative analysis will be illustrated by reanalyzing a case study considered by Barker (1986).     

经济转型期的企业家机制:概念、运作及其重构

运用现代经济学与管理学的若干理论，对经济转型期我国企业家机制运行中存在的问题进行分析，在对企业家的定义、企业家与环境的互动关系、企业家机制与企业制度和市场机制的关系进行分析后，针对我国当前企业家机制的重构问题提出了一些原则性建议     

“语音信号处理”双语教学的探索——以合肥工业大学为例

作为新的教学形式,双语教学中有许多值得讨论和有待于探索的问题。文章对＂语音信号处理＂双语教学实践过程中的语音处理技术的应用、多媒体手段的使用、原版教材的合理组织以及通过做＂课程项目＂和＂陈述＂培养学生自主式学习能力等具体实施方法进行了初步的探索。     

宽带侦察信号检测中的门限算法

利用接收频谱不同噪声子带的独立同分布特性,讨论了通信侦察中信号检测的自适应门限算法.以接收信号DFT输出幅度平方作为统计量时,按指数分布特征计算门限;以DFT幅度平方的积累值作为统计量时,按卡方分布或恒虚警处理计算门限.根据不同统计量服从某一概率分布的特性,上述方法可统一为基于噪声谱线直方图统计的方法,并针对有色噪声频谱提出了一种基于形态学开运算的谱线处理方法.理论分析与仿真实验验证了算法的有效性.     

Nonverbal Communication in Humans

Nonverbal behavior includes all communicative acts except speech. Communication means conveying information through signals. We use body language without being aware of it, perceive and interpret other people's body language. Three classes of nonverbal behavior are the verbal-vocal, nonverbal-vocal, and nonverbal-nonvocal. Several gestures illustrate the relationship between verbal and nonverbal behavior. Nonverbal phenomena are most important in the structuring and occurrence of interpersonal communication and the movement-to-movement regulation of the interaction. Nonverbal signs help regulate the system, cueing hierarchy and priority among communicators, signaling the flow of interaction, and providing meta-communication and feedback. Experiences teach us unconsciously that space communicates.     

New robust estimators for detecting non-random patterns in multivariate control charts: a simulation approach

In the past decade, different robust estimators have been proposed by several researchers to improve the ability to detect non-random patterns such as trend, process mean shift, and outliers in multivariate control charts. However, the use of the sample mean vector and the mean square successive difference matrix in the T ² control chart is sensitive in detecting process mean shift or trend but less sensitive in detecting outliers. On the other hand, the minimum volume ellipsoid (MVE) estimators in the T ² control chart are sensitive in detecting multiple outliers but less sensitive in detecting trend or process mean shift. Therefore, new robust estimators using both merits of the mean square successive difference matrix and the MVE estimators are developed to modify Hotelling's T ² control chart. To compare the detection performance among various control charts, a simulation approach for establishing control limits and calculating signal probabilities is provided as well. Our simulation results show that a multivariate control chart using the new robust estimators can achieve a well-balanced sensitivity in detecting the above-mentioned non-random patterns. Finally, three numerical examples further demonstrate the usefulness of our new robust estimators.