一种适用于有限长度混合相位未知脉冲的最小平方反褶积新方法

普通的最小平方反褶积只有在子波为最小相位脉冲和反射序列为白噪声的假设下才是成立的,而对于混合相位未知脉冲来说,这种最小平方反褶积就不再适用了。本文提出一种适合于有限长度混合相位未知脉冲的最小平方反褶积方法。运用此法只需预先估计一个混合相位子波的长度。合成数据的试验结果表明,该方法有较好的效果,且对预先估计出的子波长度不敏感。文中还证明混合相位未知脉冲最小平方反褶积等效于一种有间隙的平滑误差滤波器的作用,而这种有间隙的平滑误差滤波又可分解为一个前向多步预测误差滤波与一个后向多步预测误差滤波之和。可以预计这种新的反滤积方法将在地震数据处理中得到有效的应用。     

A genetic‐based neuro‐fuzzy controller for blind equalization of time‐varying channels

This paper presents a neuro‐fuzzy network (NFN) where all its parameters can be tuned simultaneously using genetic algorithms (GAs). The approach combines the merits of fuzzy logic theory, neural networks and GAs. The proposed NFN does not require a priori knowledge about the system and eliminates the need for complicated design steps such as manual tuning of input–output membership functions, and selection of fuzzy rule base. Although, only conventional GAs have been used, convergence results are very encouraging. A well‐known numerical example derived from literature is used to evaluate and compare the performance of the network with other equalizing approaches. Simulation results show that the proposed neuro‐fuzzy controller, all parameters of which have been tuned simultaneously using GAs, offers advantages over existing equalizers and has improved performance. From the perspective of application and implementation, this paper is very interesting as it provides a new method for performing blind equalization. The main contribution of this paper is the use of learning algorithms to train a feed‐forward neural network for M‐ary QAM and PSK signals. This paper also provides a platform for researchers of the area for further development. Copyright © 2008 John Wiley & Sons, Ltd.     

运用PLC技术改造385m~2凯利式叶滤机控制系统

根据生产实践 ,结合PLC的技术特点和 385m2 凯利式叶滤机的电气联锁特性 ,阐述了应用PLC技术 ,可进一步提高 385m2 凯利式叶滤机的运转率和自动化水平。     

Sediment Concentration and Its Prediction by Perceptron Kalman Filtering Procedure

Predictions of the discharge and the associated sediment concentration are very useful ingredients in any water resources reservoir design, planning, maintenance, and operation. Although there are many empirical relationships between the discharge and sediment concentration amounts, they need estimation of model parameters. Generally, parameter estimations are achieved through the regression method (RM), which has several restrictive assumptions. Such models are locally valid and their structures and parameter values are questionable from region to others. This paper proposes a new approach for sediment concentration prediction provided that there are measurements of discharge and sediment concentration. The basis of the methodology is a dynamic transitional model between successive time instances based on two variables, namely, discharge and sediment concentration measurements. The transition matrix elements are estimated from the measurements through a special form of the artificial neural networks as perceptrons. The sediment concentration predictions from discharge measurements are achieved through a perceptron Kalman filtering (PKF) technique. In the meantime, this technique also provides temporal predictions. A certain portion of the measurement sequence is employed for the model parameter estimations through training and the remaining part is used for the model verification. Detailed comparisons between RM and PKF approaches are presented and, finally, it is shown that the latter model works dynamically by simulating the observation scatter diagram in the best possible manner with smaller prediction errors. The application of the methodology is performed for the discharge and sediment concentration measurements obtained from the Mississippi River basin at St. Louis, Missouri. It is found that the PKF methodology has smaller average relative, root-mean-square, and absolute errors than RM. Furthermore, graphical representation, such as the scatter and frequency diagrams, indicated that the PKF approach has superiority over the RM.     

如何提高电子产品的可靠性

主要介绍了电子产品在研制、生产、试验中的可靠性工作。     

Probabilistic linear models for multiresolution estimation in gray-level images

A multiresolution analysis of digital gray-level images is presented. A gray-level multi-scale framework is determined from two main assumptions: the gray scale is binary at the finest spatial resolution, and the gray levels of composed regions are obtained additively. In order to interrelate the gray-level histograms of the same image at different resolutions, probabilistic linear models are developed, which are then applied for estimation. Linear-optimization theory is used as a way of constructing such models. A general procedure for image processing is sketched, based on gray-level estimation. A versatile algorithm for nonlinear filtering is derived. Some examples of prospective applications are given.This work was partially supported by grant TIC91-646 from the DGYCIT of the Spanish Government.     

Multi‐layered flat‐surface micro‐optical components directly molded on an LCD panel

Abstract— We have developed a process to fabricate optical components, such as a lens, prism, or diffuser, directly on to a glass substrate. Processes include precision mastering by diamond cutting and multi‐layer photopolymer (2P) molding to realize flat surfaces and the integration of multiple components with an alignment within a few micrometers.     

弹性筛管防砂技术

弹性筛管防砂技术是根据稠油油藏高轮次吞吐和蒸汽驱井防砂生产需要而研制的筛管防砂新技术。进行了筛管结构优化、加厚过滤单元外罩设计、固定方式研究、弹性过滤材料筛选、防腐实验研究等。室内试验表明，筛管的过流能力在900cm^2／m以上、渗透率在100μm^2以上、筛管抗内、外压强度达到20MPa、防砂粒径在0.1mm以上、耐温350℃、pH值在3～12之间不被腐蚀。现场试验证明，该技术防砂和抗堵塞性能好，防砂有效期长，地层适应性强，施工简便，防砂生产效果明显，具有良好的应用前景。     

基于MOCCⅡ多功能滤波器的设计

本文简要介绍了Mulitple-output CCⅡ（简称MOCCⅡ）器件的电路特性，提出了一个新颖的基于MOCCⅡ多功能滤波器的电路。该电路可同时实现一阶低通以及二阶低通、高通、带阻、全通和带通等输出。经分析，该电路具有很低的灵敏度。电路中所有RC元件均接地，便于集成等优点。