超深亚微米信号串扰分析

芯片设计进入深亚微米后,互连线效应(主要是信号串扰)对集成电路的影响越来越大。该文针对这种影响进行了分析,讨论了在不考虑耦合电容和考虑耦合电容的两种情况下噪声产生机理,建立了一个耦合电容分析模型,得出了噪声产生的原因,并提出了解决噪声的策略。根据设计实例并结合建立的模型,提出了实际芯片设计中有效地控制串扰的方法,取得了良好的效果。     

采用二阶特征窗的语音盲分离方法

利用语音信号的短时平稳特性,提出了一种二阶特征窗语音盲分离方法。该方法采用新的联合差分相关矩阵白化算法去除有色噪声影响;用长度等于语音信号基音周期的等距特征窗连续分割预白化观测数据,在每个加窗的数据帧计算不同的时滞协方差矩阵。利用联合近似对角化时滞协方差矩阵集合得到旋转参数,最终达到语音信号的盲分离。该方法消除了有色噪声的影响,只需用到二阶信息就能很好地分离语音信号。仿真实验验证了该方法的有效性。     

Heteroscedastic Regression Models and Applications to Off-line Quality Control

We discuss in the present paper the analysis of heteroscedastic regression models and their applications to off-line quality control problems. It is well known that the method of pseudo-likelihood is usually preferred to full maximum likelihood since estimators of the parameters in the regression function obtained are more robust to misspecification of the variance function. Despite its popularity, however, existing theoretical results are difficult to apply and are of limited use in many applications. Using more recent results in estimating equations, we obtain an efficient algorithm for computing the pseudo-likelihood estimator with desirable convergence properties and also derive simple, explicit and easy to apply asymptotic results. These results are used to look in detail at variance minimization in off-line quality control, yielding techniques of inferences for the optimized design parameter. In application of some existing approaches to off-line quality control, such as the dual response methodology, rigorous statistical inference techniques are scarce and difficult to obtain. An example of off-line quality control is presented to discuss the practical aspects involved in the application of the results obtained and to address issues such as data transformation, model building and the optimization of design parameters. The analysis shows very encouraging results, and is seen to be able to unveil some important information not found in previous analyses.     

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.     

高可用性系统的研究与实现

研究了高可用系统的结构，介绍了一种高可用系统的实现。在分析系统失效因素和高可用系统结构的基础上，对主要的失效部分（软硬件）进行冗余以提高服务器、磁盘、网络可靠性，据此采用有效的失效探测与恢复机制，实现了一个能够保证整机容错，无单点失效的高可靠系统。     

离散频谱分析的一种新校正方法

提出了一种对幅值谱进行校正的新方法,用以解决离散频谱当谱峰没有对正峰顶,有能量泄漏所带来的误差,并讨论了矩形窗、汉宁窗、海明窗和高斯窗四种窗函数的修正方法,校正的频率、幅值和相位的精度可达细化100倍以上的效果。     

空间谱估计测向实验系统

空间谱估汁测向具有许多优异的性能，已得到理论分析和大量计算机模拟结果的支持。本文简要介绍一种空间谱估计测向实验系统的情况，包括测向原理、系统组成、关键技术问题分析和外场试验情况及试验结果等。实验表明，这种新型测向系统的确具有优异的性能和良好的工程实验前景。     

频率捷变信号的频率／方向联合估计

提出一种利用并行阵列数据联合估计频率捷变信号（ＦＡＳ）的频率和ＤＯＡ算法。这种算法能同时估计频率和ＤＯＡ，并自动地将它们配对，从而识别不同的ＦＡＳ。计算机模拟结果表明这种算法是有效的。