机器人CO2焊接视觉跟踪实时控制研究

本文在对采用ＣＣＤ摄象机正面拍摄焊接区图象并用微机进行图象处理，以及对视觉跟踪采用实时控制的必要性分析的基础上，通过实验建立了一个实用的机器人ＣＯ_２保护焊自适应控制系统。试验表明该系统能成功地避开焊接时短路过渡的干扰，获得满意的焊接区图象，满足机器人弧焊实时控制的要求．     

加工贸易对我国贸易增长的贡献

我国加工贸易形式从大的方面讲分为来料加工和进料加工两种形式。改革开放27年来,我国加工贸易得到了飞速发展。并且,我国成为在国际贸易体系中具有影响力的贸易大国,主要得益于加工贸易的发展。     

ODP环境中全局安全系统内的安全域之间的联接

ＯＤＰ环境中的全局安全系统在逻辑上是由各个安全域迈过安全联接互联而成的。安全城之间的关系、全局安全系统的结构却是错综复杂的。安全域之间能否建立联接，怎样建立联接，是由安全域之间的关系所决定的。在全局安全系统的格模型的基础上，讨论了全局安全系统的结构、安全域之间的关系、以及安全域之间的联接模型。     

阵列信号单信道处理技术

阵列信号处理已广泛应用于许多电子系统中，如微波无源比幅测向系统等，但通道间的振幅和相位的不平衡常常引起较大的测向误差。为了匹配通道间的振幅和相位平衡，可利用卫星通信中的多址联接技术（如ＦＤＭＡ、ＴＤＭＡ或ＣＤＭＡ）构成单信道处理系统来代替多信道系统。文中详细地研究了ＣＤＭＡ单信道系统，建立了系统模型，分析了系统特性，模拟结果证明了这种单信道理论和技术的可行性。     

一种瞬变步长LMS自适应滤波算法

基于规一化起动、平滑递推和ＰＬＳ算法导出了一种新的变步长ＬＭＳ算法。文中分析了起动后的平稳连接和提高起始收敛速度的条件，证明了步长因子μ（ｋ）的瞬变特性及其对减小失调噪声的作用。计算机仿真效果较好，支持了理论分析。     

优化TOPSIS模型在木材加工企业的评价应用——基于SCM视角

考虑到林产品经销商在参与木材加工企业构建供应链时需选取其作为上游合作伙伴,构建包括竞争力、绿色行为、质量、成本和交货期5个一级指标及其14个二级指标的评价指标体系,运用TOPSIS优化改进模型,结合模糊数学评价木材加工企业,最后通过案例证实该评价指标体系的可行性,为林产品经销商提供参考借鉴。     

二语作格动词语义加工中的身物交互效应

This article investigates the theoretical basis and feasibility in the processing of English ergative verbs from the perspective of body-object interaction effects (BOI). It analyzes the motor degree of different verbs, probing into the semantic features and syntactic behaviors of ergative verbs. It also explores the relationships between the BOI effects and different type of verbs in semantic processing, examining the motor prominence of English ergative verbs, as well as analyzing the factors that cause the misusage of English ergative verbs in the second language processing. Further empirical research is needed to verify the BOI effects’ restrictive elements in the processing of English ergative verbs.     

A Compressive Sensing Based Analysis of Anomalies in Generalized Linear Models

In this article, we present a compressive sensing based framework for generalized linear model regression that employs a two-component noise model and convex optimization techniques to simultaneously detect outliers and determine optimally sparse representations of noisy data from arbitrary sets of basis functions. We then extend our model to include model order reduction capabilities that can uncover inherent sparsity in regression coefficients and achieve simple, superior fits. Second, we use the mixed ?₂/?₁ norm to develop another model that can efficiently uncover block-sparsity in regression coefficients. By performing model order reduction over all independent variables and basis functions, our algorithms successfully deemphasize the effect of independent variables that become uncorrelated with dependent variables. This desirable property has various applications in real-time anomaly detection, such as faulty sensor detection and sensor jamming in wireless sensor networks. After developing our framework and inheriting a stable recovery theorem from compressive sensing theory, we present two simulation studies on sparse or block-sparse problems that demonstrate the superior performance of our algorithms with respect to (1) classic outlier-invariant regression techniques like least absolute value and iteratively reweighted least-squares and (2) classic sparse-regularized regression techniques like LASSO.     

A NOTE ON ESTIMATING THE NUMBER OF SUPERIMPOSED EXPONENTIAL SIGNALS BY THE CROSS-VALIDATION APPROACH

In this paper, a procedure based on the delete-1 cross-validation is given for estimating the number of superimposed exponential signals, its limiting behavior is explored and it is shown that the probability of overestimating the true number of signals is greater than a positive constant for sufficiently large samples. Also a general procedure based on the cross-validation is presented when the deletion proceeds according to a collection of subsets of indices. The result is similar to the delete-1 cross-validation if the number of deletions is fixed. The simulation results are provided for the performance of the procedure when the collections of subsets of indices are chosen as those suggested by Shao [1] Shao, J. 1993. Linear model selection by cross-validation. J. Amer. Statist. Assoc., 88: 486–494. [Taylor & Francis Online], [Web of Science ®] , [Google Scholar]in a linear model selection problem.     

Aspects of Statistical Computing: What Packages for the 1980's Ought to Do

A wish list of desirable statistical computing capabilities is presented. This may help one question which of these capabilities can be satisfied by existing packages, which might be met through reasonable extensions to these packages, which might require substantial new development, and which ought to be supplied by the computing environment rather than the packages. These questions are explored, taking into account the nature of the statistical work and the choices presented by technology. Attention is given to the barriers to be overcome if future statistical packages are to take full advantage of new technology.