高功率脉冲水中放电的应用及其发展

首先介绍了高功率脉冲水下放电的机理，然后综合论述了其应用和研究的状况，从较为成熟的脉冲水处理技术到医疗领域的ESWL应用技术，以及在脉冲电场食品杀菌和水下目标探测方面的最新发展和研究，最后指出了高功率脉冲电技术应用前景以及进行更系统和深入研究的必要性。     

A New Approach for Built‐in Self‐Test of 4.5 to 5.5 GHz Low‐Noise Amplifiers

This paper presents a low‐cost RF parameter estimation technique using a new RF built‐in self‐test (BIST) circuit and efficient DC measurement for 4.5 to 5.5 GHz low noise amplifiers (LNAs). The BIST circuit measures gain, noise figure, input impedance, and input return loss for an LNA. The BIST circuit is designed using 0.18 μm SiGe technology. The test technique utilizes input impedance matching and output DC voltage measurements. The technique is simple and inexpensive.     

子空间方法盲多用户检测技术分析与探索

着重分析了基于子空间跟踪的盲线性多用户检测算法 ,并对其内部算法模块进行了仿真比较 ,最后对算法性能改善方法提出了自己的新思路     

海杂波中基于混沌预测的目标检测方法改进

基于记忆库非线性预测的NP-CFAR方法是目前混沌海杂波背景中目标检测的一种典型而先进的方法.考虑到海杂波功率与特征的时变不稳定性,本文提出运用旋转超盒分类取代这一方法中的NP-CFAR进行目标检测,并探讨了运用盒维数特征提取进行预处理以节省运算开销的问题.仿真实验验证了本文所提改进方法的有效性.     

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 Combined Antenna Array and Multi-User Detection DS-CDMA Receiver in Single-Path and Multi-Path Fading Channels

An adaptive antenna array is incorporated into a decorrelatingmulti-user detector to effectively increase the DS-CDMA system capacity.Capacity improvement is due to beamforming gain, spatial diversity gain(assuming large angle spread), and the decorrelating effect. Thereceiver has been analyzed for the cases of sufficiently andinsufficiently spaced receiving antennas. The receiver consists of afront-end beamformer for every user in the cell and has knowledge of allusers' signature sequences. The beamformer estimates the desired userchannel vector, enhancing its signal and reducing the co-channelinterference from other directions. The multi-user detection, exploitingknowledge of other users, rejects those interferers whose arrival anglesare close to that of the desired user. The average uncoded Bit ErrorRate (BER) as a function of the number of in-beam active users, theaverage antenna Signal-to-Noise Ratio (SNR), and the number of receivingantennas is examined in both single-path and multi-path Rayleigh fadingchannels. Analysis shows an increase in system capacity proportional tothe number of receiving antennas.     

一种新颖的表面等离子谐振效应光波导水质传感技术

光学表面等离子谐振（ＳＰＲ）效应是一种很有效的水质检测技术，经过详细的理论推导，同了ＳＰＲ反射光强的普遍适用公式。在纯水与受污染水两种情况下，根据一些已知参数计算出结果。由计算结果数据一出的曲线比较表明，ＳＰＲ效应在两种情况下有明显差别，这也正是ＳＰＲ效应用于水质检测的理论根据。     

Outlier-resistant methods for estimation and model fitting

Least squares is perhaps the most widely used technique for model fitting. In this article, we illustrate the poor performance of least squares when there are spurious values, or outliers, in a sequence of measurements. A brief overview of three well-known classes of robust alternatives to the least-squares mean is presented. For robust regression, a recent proposal called least median squares (LMS) is decribed. LMS regression is compared to least-squares regression in an example involving the estimation of optical fiber geometry. References are provided for software that is available for robust estimation techniques surveyed in this article.     

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.     

COLLISION DETECTION AMONG MOVING OBJECTSIN MACHINING PROCESS SIMULATION

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