基于WVD的防空雷达直升机信号特征分析

基于直升机目标旋转部件的调制模型，本文针对防空雷达提出了分析直升机信号特征的一种新方法——WVD法，并对直升机目标旋转部件调制回波信号在不同噪声情况下加以仿真分析，结果表明：用WVD分析雷达回波中直升机信号特征是一种非常有效的方法。     

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.     

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。     

Integrated Smart Sensor Calibration

In many applications electronic sensors are used toimprove performance and reliability of measurement systems. Suchsensors should provide a correct transfer from the physical signalto be measured to the electrical output signal. One importantstep to achieve this, is to calibrate each sensor by applyingdifferent reference input signals and adjusting the sensor transferaccordingly. Besides expensive reference equipment the calibrationprocess takes much time and attention per individual sensor,which means a considerable increase in sensor production costs.By including at the sensor or sensor interface chip a programmablecalibration facility the calibration of such smart sensors caneasily be automated and can be executed for a batch of sensorsat a time, thus minimizing the calibration time and costs. Thispaper presents a calibration method and options for integrationin the smart sensor concept, in hardware as well as in software.An advantage of the proposed method is that it does not needa large matrix of calibration data, which needs to be storedin a look-up table or converted into a correction formula, butinstead it uses a step-by-step approach to correct the sensortransfer at each calibration measurement until the error is sufficientlysmall.     

无线电引信多普勒信号增速器的研究

论述了无线电引信多普勒信号增速器的实现原理及意义，介绍了采用ＴＭＳ３２０Ｃ３０作为ＣＰＵ、多片大容量静态ＲＡＭ芯片构成海量存储体的信号增速器硬件结构和软件设计，并提出了今后的研究方向。     

Tracking Control and Synchronization for Two-Dimension Discrete Chaotic Systems

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中央电视台第一个数字化演播室视频系统介绍

数字电视系统在提高图像质量方面已显示出极大的优越性。因此，世界各国电视台都已开始数字化的进程，中国也不例外。本文详细介绍了中央电视台第一个数字化演播室－８００ｍ＾２演播室的视频系统，包括视频系统数字信号格式的确定，主要设备的特点以及演播室数字视频系统的主要特点等，供广大同行参考。     

微机对调制信号的包络解调

应用检相原理，可以提取有限长度调制信号和包络解调。通过改变Ａ／Ｄ转换器的位数，提高检相分辨率，它与检测对象的速度无关。这为提高检相分辨率展示了新的途径。     

Diagnostics and monitoring of complex production processes using measurement of vibration-acoustic signals

A vibration-acoustic method for diagnostics and monitoring of production processes such as cutting metals makes it possible compared with other methods to reduce the requirement for measuring equipment and it provides a computer representation of the results observed. The set of equipment suggested has low cost and it exhibits considerable flexibility compared with existing equipment. __________ Translated from Izmeritel’naya Tekhnika, No. 7, pp. 30–34, July, 2006.     

RSFM网络及其在信号滤波中的应用

介绍了一种适用于模式识别的新型神经网络模型--局部有监督特征映射（Reglonal Supervised Feature Mapping,RSFM）网络,描述了该网络的拓扑结构和学习算法,研究了网络的基本性能,最后将其应用到了信号滤波中.理论研究和仿真实验表明,该网络结构简单、算法简洁,收敛速度快、识别精度高,适用于需要大样本训练、随机干扰严重的复杂模式的分类与识别.