机车大功率整流管试验台的研制

本文基于计算机技术和现代测量技术，介绍了一种虚拟仪器-机车大功率整流管试验台的研制。该试验台根据LMS自适应算法，模拟实际工作环境，自适应地控制试验过程，并对试验数据应用小波分析技术分析处理，得到机车大功率整流管准确而全面的性能参数，具有自动化程度高、试验结果可靠性高的优点。本文主要介绍试验数据处理和软件设计。     

ISIS全局优化多道反演技术在墩2块岩性油藏描述中的应用

为进一步落实墩2块戴一段岩性油藏成藏规模及分布规律，针对该储层薄、横向变化快的特点，利用ISIS全局优化多道反演技术，对该构造区岩性储层进行了精细描述，较好的预测出戴一段储层平面分布规律。     

微波宽频带功率负载的研究

介绍了５００Ｗ宽频带功率负载的设计及实验结果，并将研究成果扩展到１０～１０００Ｗ范围。负载主要技术指标：输入阻抗５０Ω，频带宽度０～１０００ＭＨｚ，电压驻波比≤１．１．表面最高温升△ｔ≤１００℃。     

基于小波变换的医学图象压缩编码

本文研究了医学图象小波变换系数的统计特征。根据医学图象的特点，提出了基于小波变换的医学图象编码方法。实验表明，这种方法具有较好的压缩编码性能，优于JPEG标准。同时，它支持逐次浮现式传输，从而能满足医学图象存储、通信、检索的需要。     

综合应用地震属性、测井数据反演储层参数

本文研究了样点地震属性的特征提取，利用BP神经网络建立测井声波时差和地震属性的非线性映射关系。采用距离加权平均对研究区所有井的反演结果进行外推。为了提高分辨率和计算结果的准确性，详细分析、研究了适合于地震信号分解和重构的小波，以及测井声波时差和地震波阻抗与层界面的关系。最后，对反演的声波时差资料进行界面影响校正，进而计算出较符合实际情况的孔隙率参数。经已知井和新钻井验证，计算结果和实际情况相一致，效果令人满意。     

小波分析及其在时变滤波和信号分离中的应用

利用小波变换具有的多时频分辨率特性，对地震勘探和测井信号这类非平衡信号进行分析，可以充分利用信号的时间－频率特性。文中介绍了小波变换的基本概念及其在地震勘探信号的时变滤波和声波全波列测井信号的信号分离中的应用，实例表明，小波变换在地球物理信号中具有广阔的应用前景。图５参７     

The mechanics of compressive kinking in unidirectional fiber reinforced ductile matrix composites

Three distinct stages of kink band formation and propagation exist in ductile matrix composites subjected to compressive loading. These stages are called incipient kinking, transient kinking and kink band broadening. Each stage involves a different deformation mode. The mechanics governing each stage are discussed. Incipient kinking, where the peak load is attained, and kink band broadening, where the load attains a steady-state, are important in structural design. Two design philosophies are presented. References to pertinent literature are made throughout.     

A New Matlab De-noising Algorithm for Signal Extraction

The goal of a de-noising algorithm is to reconstruct a signal from its noise-corrupted observations. Perfect reconstruction is seldom possible and performance is measured under a given fidelity criterion. In a recent work, the authors addressed a new Matlab algorithm for de-noising. A key method of the algorithm is selecting an optimal basis from a library of wavelet bases for ideal de-noising. The algorithm with an optimal basis from a library of wavelet bases for de-noising was created through making use of Matlab＇s Wavelet Toolbox. The experimental results show that the new algorithm is efficient in signal de-nosing.     

Use of a neural network to link AFM etch patterns to plasma parameters

Plasmas play a critical role in depositing thin films or etching fine patterns while manufacturing integrated circuits. A new model for plasma diagnosis is presented. This was accomplished by linking atomic force microscopy (AFM) to plasma parameters using a neural network. Experimental AFM data were collected during the etching of silicon oxynitride films in C₂F₆ inductively coupled plasma. Surface roughness of etched patterns was characterized by means of discrete wavelet transformation. This led to the construction of three vertical (type I), diagonal (type II), and horizontal (type III) wavelet coefficient-based models. The performance of diagnosis models was evaluated in terms of the prediction and recognition accuracies. Both accuracies were optimized as a function of the number of hidden neurons. Comparisons revealed that the type I model yielded the largest recognition and the smallest prediction error. This was demonstrated even under stricter monitoring conditions. More improved diagnosis is expected by enhancing AFM resolution.     

双谱估计在导引头信号检测与处理中的应用

双谱估计是一种应用广泛的高阶谱估计。将双谱估计应用于超宽带导引头信号检测与处理系统中,为导引头信号处理中的平滑和滤波增添了一种新的方法。仿真结果表明该方法是有效的。