Study on the Complexity of the Bullwhip Effect

Recent years have witnessed a rapid growth of interest in the study of the dynamic behavior of replenishment rules of bullwhip effect. We prove that bullwhip effect and butterfly effect share a same the self-oscillation amplifying mechanism that is the ordering decisions the supplier self-oscillation amplify the perturbations brought by the errors in the processing of retailers' demand information. This results as an explicit self-similar structure of the sensitivity of the system to the initial values duty to the nonlinear mechanism. In this paper, the causes process of the bullwhip effect is described as the internal nonlinear mechanism and study on the complexity of bullwhip effect for order-up-to policy under demand signal processing. The methodology is based on fractal and chaotic theory and allows important insights to be gained about the complexity behavior of bullwhip effect.     

异步DS-CDMA系统中基于矩阵点除算法的DOA估计

针对异步DS-CDMA系统中的多用户环境,本文提出了一种低复杂度的DOA估计算法——矩阵点除算法。该算法通过对感兴趣信息的逐次分离,实现了DOA的逐路径估计。算法具有两方面显著优势:(1)克服了传统的DOA估计算法在路径总数大于天线阵元数时不能工作这一缺陷:(2)避免了计算复杂的特征值分解运算,大大降低了算法复杂度。仿真实验验证了算法的有效性。     

现场总线技术在城市污水处理与气象中的应用

文章主要讨论了LonWorks现场总线技术在城市污水处理厂和气象指数预报中的应用。采用IPC和PLC控制结构对现场的各种设备实现控制和数据的采集，通过现场总线网络传输数据到中心控制室或远程终端，实现污水处理的自动控制和气象信息的实时采集和处理。     

Image processing using cellular neural networks based on multi-valued and universal binary neurons

Multi-valued and universal binary neurons (MVN and UBN) are the neural processing elements with the complex-valued weights and high functionality. It is possible to implement an arbitrary mapping described by partially defined multiple-valued function on the single MVN. An arbitrary mapping described by partially defined or fully defined Boolean function, which can be non-threshold, may be implemented on the single UBN. The quickly converging learning algorithms exist for both types of neurons. Such features of the MVN and UBN may be used for solving the different problems. One of the most successful applications of the MVN and UBN is their usage as basic neurons in the Cellular Neural Networks (CNN). It opens the new effective opportunities in nonlinear image filtering and its applications to noise reduction, edge detection and solving of the super resolution problem. A number of experimental results are presented to illustrate the performance of the proposed algorithms.An erratum to this article can be found at     

基于FPGA并行处理的实时图像相关速度计

研究制作了一种采用高速线阵CCD的实时相关速度计,其测量数据的输出速率可达每秒一万次。针对以往光学相关测速方法的问题进行了讨论,探讨了适合FPGA并行处理的算法,制作了高速线阵CCD摄像机及其处理装置。通过实验验证了系统的可行性和可实现性。     

瑞利与非瑞利杂波背景下单、双参数杂波图的性能分析

对瑞利和非瑞利杂波中的单、双参数杂波图的控制虚警性能和检测性能进行了比较分析，并得到了双参数杂波图门限调整值的取值范围，得出了几点有益的结论。     

非等间距序列建模过程中存在的问题及改进

在研究非等间距序列的基础上 ,本文将非等间距累加运用于非等间距序列的建模过程中 ,使原有模型得到改进 .实例表明 ,改进后模型的精度有了很大提高     

星上多载波解调技术研究

新一代具有星上处理的卫星将急剧降低地球站的复杂度,星上多载波解调(MCD)技术就是在星上分离出各个信道然后再独立解调。研究了星上多路信号即FDMA/QPSK信号的多载波技术,这是一种重要的星上处理技术,它包括频分多路信号的FFT分路算法、频偏估计、多路QPSK信号的全数字化解调算法和解调算法中的位定时恢复方法等。对主要的关键技术进行了计算机仿真。     

小波提升算法及其在图像处理中的应用

小波提升算法是一种新的双正交小波构造方法，通过预测算子，确定高频信息，并初步确定低频信息，然后通过更新算子，对初步确定的低频信息进行修正，从而确定低频信息。它在空域对信号进行变换，完成了对信号频域的分析。在图像处理中，基于离散小波变换的提升算法比传统的卷积算法运算简单，实时性好，易于实现，因而被新一代图像压缩标准JPEG2000所采用。文中简要介绍了小波提升算法的原理，分析了其特点，并介绍了JPEG2000标准中采用的W5／3、D9／7两种小波的提升格式和实现算法。     

通信瓶颈下的实时并行任务分配研究

提出了实时并行任务粒度划分的具体设计方法，采用了系统内通信迟延最小的约束条件进行多处理器上的任务分配，解决了高速实时信号处理中的数据通信瓶颈问题。在自行设计的超立方体结构的通用信号处理机上，实现了空时二维自适应信号处理和SAR实时成像，显著减小了数据通信迟延，提高了并行效率和性价比。