Signal Integrity: Fault Modeling and Testing in High-Speed SoCs

As we approach 100 nm technology the interconnect issues are becoming one of the main concerns in the testing of gigahertz system-on-chips. Voltage distortion (noise) and delay violations (skew) contribute to the signal integrity loss and ultimately functional error, performance degradation and reliability problems. In this paper, we first define a model for integrity faults on the high-speed interconnects. Then, we present a BIST-based test methodology that includes two special cells to detect and measure noise and skew occurring on the interconnects of the gigahertz system-on-chips. Using an inexpensive test architecture the integrity information accumulated by these special cells can be scanned out for final test and reliability analysis.     

A Neural Network Approach for Signal Detection in Digital Communications

In this paper, we propose a new approach for signal detection in wireless digital communications based on the neural network with transient chaos and time-varying gain (NNTCTG), and give a concrete model of the signal detector after appropriate transformations and mappings. It is well known that the problem of the maximum likelihood signal detection can be described as a complex optimization problem that has so many local optima that conventional Hopfield-type neural networks fail to solve. By refraining from the serious local optima problem of Hopfield-type neural networks, the NNTCTG makes use of the time-varying parameters of the recurrent neural network to control the evolving behavior of the network so that the network undergoes the transition from chaotic behavior to gradient convergence. It has richer and more flexible dynamics rather than conventional neural networks only with point attractors, so that it can be expected to have much ability to search for globally optimal or near-optimal solutions. After going through a transiently inverse-bifurcation process, the NNTCTG can approach the global optimum or the neighborhood of global optimum of our problem. Simulation experiments have been performed to show the effectiveness and validation of the proposed neural network based method for the signal detection in digital communications.     

子波变换理论及其在信号处理中的应用

子波分析的形成是傅里叶分析发展史上里程碑式的进展，子波分析优于傅里叶交换的地方在于它在时域和频域同时具有良好的局部化性质，从而可以把分析的重点聚焦到任意的细节，被人们誉为数学显微镜，成为近年来在工具和方法上的重大突破。本文将子波理论中的主要定理、结论、变换特性和一些重要概念加以综述，以促进子波理论的应用。本文的重点在于介绍多分辨率分析和子波分析及其实现、子波变换及其算法、子波和滤波器组等的重要内容，并介绍其在信号处理中的应用及研究动态。     

模拟信号的恢复及其误差研究

数模混合仿真中模拟信号的恢复及其误差对整个仿真过程具有重要影响。本文探讨了用零阶保持和一阶保持进行信号恢复的方法，比较了它们的误差及工作特点。特别指出了一阶保持中，由于存在积分器复原时间及数字机操作时间的影响而会带来附加的误差，因此一阶保持方法较难达到其理论的精度。     

Windows下的数据采集和A/D转换

主要论述了使用Visual C 6.0在Windows下实现数据的实时采集和信号的图形显示，其中包括数据采集、A／D转换以及信号的实时显示等。使用面向对象的编程方法，构造了一个通用的A／D转换类，具有很好的可重用性。     

基于充放电原理实现的微电容测量电路

具有抗分布电容以及简单实用等特性的充放电电路是目前微电容测量中广泛采用的一种测量电路。本文对基于充放电原理的微电容测量电路进行了深入研究，并介绍一种基于充放电原理的实用电路。     

回转升降生物接触工艺的实验研究

提出了一种具有特殊运转方式的新型RBC系统－－回转升降生物接触工艺，对回转升降生物接触工艺的工作原理和工艺特征进行了论述。并通过动态实验，对回转升降生物接触工艺小型实验装置的性能和效果进行了初步考察。     

Occupational airway diseases in the metalworking industry Part 1: Respiratory infections, pneumonia, chronic bronchitis and emphysema

Occupational airway diseases are now receiving attention in industry, although study is hampered by a lack of readily-available data. The interpretation of the data that is available, and also of the root problems themselves, is itself a difficult problem. This paper has been written as a literature review which it is hoped that other researchers can take either as a starting point or as a refresher.     

复杂地区三维叠前时间偏移技术的应用

在常规地震数据处理过程中，反射波的偏移成像是基于地震数据的共深度点或共中心点叠加技术进行的，在地下地质构造相对复杂的地区，由于叠加过程的引入，导致了一些来自于大倾角地层或细微地质现象产生的地震反射信息的畸变或损失，而目前在算法上已经较为成熟的叠前偏移成像技术，便弥补了叠后偏移成像的不足，特别是在山前复杂构造区带，叠前偏移不仅能够使反射波准确成像，而且能够改善地震数据的信噪比和分辨率。     

宽带线性调频信号产主技术研究

本文介绍了采用数字基带产生结合倍频链扩展带宽的方法设计与实现了大带宽线性调频信号产生系统。详细分析研究了实现系统的三项关键技术，给出并分析了相应环节的输出信号。对系统进行了预失真补偿处理，成功实现了ＶＨＦ／ＵＨＦ波段、带宽达３００ＭＨｚ线性调频信号的产生。经脉冲压缩处理，主瓣旁瓣比（ＰＳ１Ｒ）在－３７ｄＢ以下。