MDI聚氨酯/聚硅氧烷IPN的结构与力学性能

用MDI聚醚氨酯和含少量苯基的聚二甲基硅氧烷合成了一系列的聚氨酯／聚硅氧烷IPN阻尼弹性体，研究了材料的结构与力学性能．结果表明，当聚氨酯与聚硅氧烷的质量比为90：10时。IPN的抗张强度达41．57MPa，断裂伸长率为376％，并具有良好的阻尼性能，玻璃化转变温度范围大于80℃．聚氨酯／聚硅氧烷IPN具有细微的微相分离结构，聚硅氧烷在IPN中的微相尺寸为微米级，并趋向于分布在IPN的表面．     

Determination of vitality from a non-invasive biomedical measurement for use in fingerprint scanners

Fingerprints are the oldest and most widely used biometrics for personal identification. Unfortunately, it is usually possible to deceive automatic fingerprint identification systems by presenting a well-duplicated synthetic or dismembered finger. This paper introduces one method to provide fingerprint vitality authentication in order to solve this problem. Detection of a perspiration pattern over the fingertip skin identifies the vitality of a fingerprint. Mapping the two-dimensional fingerprint images into one-dimensional signals, two ensembles of measures, namely static and dynamic measures, are derived for classification. Static patterns as well as temporal changes in dielectric mosaic structure of the skin, caused by perspiration, demonstrate themselves in these signals. Using these measures, this algorithm quantifies the sweating pattern and makes a final decision about vitality of the fingerprint by a neural network trained by examples.     

A new FMS architecture based upon networked DSP servo technology

This paper presents a critical evaluation of existing FMS architectures and the academic and industrial design and development strategies used during their formulation. The paper seeks to address the need for, and value of, existing architectures within the industrial arena. More importantly however, this paper puts forward a new two-tier distributed control architecture for FMS based upon new (real-time) networkable DSP servo control methodologies developed by one of the authors for Softronics in Australia. The ramifications of these methodologies are substantial, not only in terms of FMS control, but in the overall simplification of such systems and the development of flexible fixturing devices over the coming decade. This paper also postulates on how new FMS architectures can be developed from such technologies and details why such architectures could be more appropriate to industry needs than those that are currently in existence.     

A neural network model for fault detection in conjunction with a programmable logic controller

This paper discusses the feasibility of using neural networks as a tool in the fault detection process. A neural network is integrated with a state language programmable logic controller, an important device in an automatic control system. Time series data related to time spent in a state is gathered and used as input into a neural network, for the purpose of identifying when a fault has occurred. A feedforward neural network is used to identify which (if any) of three types of faults may have occurred. Experimental results related to sensitivity and accuracy measures are presented. A brief review of related applications and research is also presented.     

Neural networks,rational functions,and realization theory

The problem of parametrizing single hidden layer scalar neural networks with continuous activation functions is investigated. A connection is drawn between realization theory for linear dynamical systems, rational functions, and neural networks that appears to be new. A result of this connection is a general parametrization of such neural networks in terms of strictly proper rational functions. Some existence and uniqueness results are derived. Jordan decompositions are developed, which show how the general form can be expressed in terms of a sum of canonical second order sections. The parametrization may be useful for studying learning algorithms.This work was supported by the Australian Research Council, the Australian Telecommunications and Electronics Research Board, and the Boeing Commencai Aircraft Company (thanks to John Moore).     

基于CF的全集成MOSFET—C六阶低通滤波器的仿真分析

本文提出了以电流跟随器ＣＦ为基本电路元件的全集成ＭＯＳＦＥＴ－Ｃ精确连续时间六阶低通滤波器电路，并应用ＰＳＰＩＣＥ－Ⅱ通用模拟电路程序，对其幅频特性和相频特性进行了计算机仿真分析，得出了实用的结论。     

快速二阶BP网络及其在城市用水量预测中的应用

针对BP网络收敛速度慢，易导致局部极小值的缺点，提出一种快速二阶BP网络，并以城市年用水量预测为例，与BP网络对比，结果表明，该方法加快了收敛速度，提出了结果的准确度。     

一种MPEG2视频编码的神经网络自适应量化算法

本文在ＭＰＥＧ２ＴＭ５建议我自适应量化策略的基础上，提出了一种ＭＰＥＧ２视频编码的神经网络自适应量化算法。     

应用ART2人工神经网络自组织形成焊缝图象中的典型空间模式

应用ＡＲＴ２人工神经网络算法，使采集到的焊缝横截面方向上的灰度分布数据自组织形成若干种空间模式，并把它们作为典型空间模式存储在ＡＲＴ２人工神经网络的ＬＴＭ中。对实时采样到的灰度分布进行空间模式匹配程度检验，根据模式分布情况确定出焊缝位置。文中对梯度法检测结果进行了分析和比较，结果表明基于ＡＲＴ２人工神经网络的焊缝位置检测方法具有更强的噪声抑制能力，因而检测结果更准确、可靠。