一种有效的优化的多载波通信系统的功率分配算法

本文提出一种关于DMT系统传输纯数据流业务的最佳的功率分配算法，该算法使用了一种有效的表格查手工艺工和拉格朗日乘法器对分搜索办法，能够较快的收敛到最佳的功率点。同时，易于用硬件和软件实现。     

第三代短波自动链路建立系统特性分析及仿真实现

分析了第三代短波自动链路建立系统的工作特性及技术特点，并对系统仿真实现的原则及一些细节问题进行了较深入的探讨，同时对仿真实现中涉及的链路质量分析（LQA）算法进行了研究。     

An EM‐based adaptive multiple target tracking filter

Tracking targets of interest is one of the major research areas in radar surveillance systems. We formulate the problem as incomplete data estimation and apply EM to the MAP estimate. The resulting filter has a recursive structure analogous to the Kalman filter. The advantage is that the measurement‐update deals with multiple measurements in parallel and the parameter‐update estimates the system parameters on the fly. Experiments tracking separate targets in parallel show that tracking maintenance ratio of the proposed system is better than that of NNF and RMS position error is smaller than that of PDAF. Also, the system parameters are correctly obtained even from incorrect initial values. Copyright © 2001 John Wiley & Sons, Ltd.     

计算机远程控制系统的设计与实现

介绍了一个计算机远程控制系统的设计与实现，该系统采用客户机／服务器模式，实现远程屏幕的实时传输，采用LZW压缩算法对图像进行压缩传输，在接受方进行解码并且实现了远程文件创建和删除、显示被控制端的主机信息、发送实时消息等功能。采用鼠标，键盘的模拟方式对计算机进行实时控制。     

Note on ‘Construction of Double Sampling s‐Control Charts for Agile Manufacturing’

He and Grigoryan (Quality and Reliability Engineering International 2002; 18 :343–355) formulated the design of a double‐sampling (DS) s control chart as an optimization problem and solved it with a genetic algorithm. They concluded that the DS s control charts can be a more economically preferable alternative in detecting small shifts than traditional s control charts. We explain that, since they only considered the average sample size when the process is in control, their conclusion is questionable. Copyright © 2006 John Wiley & Sons, Ltd.     

A parallel and scalable algorithm for ADI method with pre-propagation and message vectorization

It is hard to implement the ADI method in an efficient way on distributed-memory parallel computers. We propose “P-scheme” which parallelizes a tridiagonal linear system of equations for the ADI method, but its effectiveness is limited to the cases where the problem size is large enough mainly because of the communication cost of the propagation phase of the scheme.

In order to overcome this difficulty, we propose an improved version of the P-scheme with “message vectorization” which aggregates several communication messages into one and alleviates the communication cost. Also we evaluate the effectiveness of message vectorization for the ADI method and show that the improved version of the P-scheme works well even for smaller problems and linear and super-linear speedups can be achieved for 8194 × 8194 and 16,386 × 16,386 problems, respectively.     

Estimation for the number of components in a mixture model using stepwise split-and-merge EM algorithm

The main difficulty with EM algorithm for mixture model concerns the number of components, say g. This is the question of model selection, and the EM algorithm itself could not estimate g. On the contrary, the algorithm requires g to be specified before the remaining parameters can be estimated. To solve this problem, a new algorithm, which is called stepwise split-and-merge EM (SSMEM) algorithm, is proposed. The SSMEM algorithm alternately splits and merges components, estimating g and other parameters of components simultaneously. Also, two novel criteria are introduced to efficiently select the components for split or merge. Experimental results on simulated and real data demonstrate the effectivity of the proposed algorithm.     

基于聚类算法实现信号盲分类

本文解决了信号处理、工业控制等领域存在的非平稳信号盲分类问题。在聚类中广泛应用的K-Means算法及其它基于中心的聚类算法有两个共同的缺陷-需要预先确定类数目且随机初始化中心引起性能不稳定。本文提出的算法较好地解决了这两个问题，提高了算法稳定性，实现了非平稳信号盲分类。提取非平稳信号的小波系数作为聚类的样本空间，分析聚类结果的统计偏差以估计类的数目，采用调和均值准则进行分类。最后给出的仿真结果表明本文提出的方法较传统的K-Means算法明显降低分类错误率。     

A fuzzy clustering algorithm enhancing local model interpretability

In this work, simple modifications on the cost index of particular local-model fuzzy clustering algorithms are proposed in order to improve the readability of the resulting models. The final goal is simultaneously providing local linear models (reasonably close to the plant’s Jacobian) and clustering in the input space so that desirable characteristics (regarding final model accuracy, and convexity and smoothness of the cluster membership functions) are improved with respect to other proposals in literature. Some examples illustrate the proposed approach.