档案自动录入及管理系统的研究

将用特定的表格形式填写的档案信息用扫描仪扫入计算机中,通过模式识别技术进行识别处理,形成文本文件,并转换成数据库文件。用VB程序设计语言编写灵活高效的档案管理系统,从而实现档案信息高效、快速、准确地录入计算机中,消除了工作中由于人的主观因素造成的错误。

基于支持向量多分类机的多类复杂手操作EEG信号模式识别

针对用于服务机器人的脑机接口系统中脑电信号模式识别精度不高,不能满足机器人多任务要求的问题,提出一种基于C-支持向量多分类机的多类复杂手操作EEG信号模式识别方法,并将其应用到复杂手操作的EEG信号模式识别试验中,实现一个4类复杂手操作的模式识别,实验结果表明,与之前用BP神经网络进行识别相比,识别率由85%提高到了90%。

基于模糊集理论的二维线性鉴别分析新方法

二维线性鉴别分析（2DLDA）是一种直接基于矩阵的特征提取方法，跳过传统的基于Fisher鉴别准则的线性鉴别分析方法中必须先将二维矩阵转化成一维矢量的过程，有效地提高了特征提取速度且避免了小样本问题，其识别率优于传统的Fisherface方法。结合模糊集理论，提出了一种新的2DLDA算法——模糊2DLDA（FIDLDA）算法。首先采用FKNN算法得到相应的样本分布信息，并按其对最后得到的特征向量所作的贡献融入到特征抽取过程中，得到有效的样本特征向量集。实验表明，F2DLDA算法的性能优于传统的2DLDA算法和Fisherface方法。

基于模糊神经网络的人脸识别方法研究

人脸识别是模式识别研究领域的重要课题,具有广阔的应用前景。本文提出了基于模糊神 经网络的人脸识别方法。首先用最优鉴别分析方法提取人脸的最优鉴别矢量集,构成特征空间,然后在 特征空间中设计模糊神经网络分类器。在ORL人脸图象库上的实验结果表明了该方法的有效性。

新模糊形态学联想记忆网络的初步研究

人工神经网络理论已经被成功地应用于各种不同的模式识别问题 .重点研究了联想记忆网络 ,提出了一种新的基于形态学和模糊运算的联想记忆网络 ,即模糊形态学联想记忆网络FMAM .它与经典联想记忆和模糊联想记忆FAM有显著不同 .文中分析了FMAM的记忆能力和抗腐蚀 /膨胀噪声的能力 .自联想FMAM具有无限存储能力 ,能保证完全回忆 ,并且回忆在一步内完成 ,可模糊性解释等 .仿真实验验证了自联想FMAM的良好性能

基于修正的最小均方误差分类算法的移动机器人运动规划

研究了不确定性环境下移动机器人躲避运动轨迹未知的移动障碍物的一种新方法．通过实时最小均方误差估计算法预测每个障碍物的位置及运动轨迹，并利用模式识别中最小均方误差分类器的修正模型计算出机器人的局部避障路径，再运用船舶导航中使用的操纵盘技术来确定每个导航周期中移动机器人的速．度仿真结果表明了该方法的可行性

混合模式识别系统研究

讨论基于多种分类方法的模块组合实现的混合模式识别系统，它不同于利用多分类器输出结果表决的集成系统．提出两个系统：一个面向印刷体汉字文本识别，另一个面向自由手写体数字识别．利用多种特征和多种分类方法的组合、部分识别信息控制混淆字判别策略以及提出的动态模板库匹配后处理方法，使系统的性能与传统单一分类器系统比较，获得明显改善．实验表明：多方法多策略混合是解决复杂和增强系统鲁棒性的一条途径

用光学阵列传感器的机器人物体分类系统

本文介绍用光学阵列传感器的机器人物体分类系统。传感器直接安装在机器人的两个手指上。被抓物体的阴影通过光导纤维传到安放在“安全区”的光敏元件上。计算机识别物体的轮廓后命令机器人抓握物体,并把它运送到指定的地点从而达到物体分类的目的。

图象噪声的模糊聚类平滑方法

模糊C-means算法在聚类分析中已得到了成功的应用,本文提出一种利用模糊C-means算法消除噪声的新方法。一般来说,图象中的噪声点就是其灰度值与其周围象素的灰度值之差超过某个门限值的点。根据这个事实,首先利用模糊C-means算法分类,再利用标准核函数检测出噪声点,然后将噪声点去掉。由于只修改噪声点处的象素灰度值,而对于其它象素的灰度值不予改变,所以本算法能够很好地保护细节和边缘。本方法每次处理3×3个点,而以往的方法只能每次处理一个点,所以本方法能提高运算速度。文中给出了利用本方法对实际图象处理的结果,并与梯度倒数权值法进行了定量的比较。

嵌入式智能图像处理在火灾预警系统的应用

传统的火灾检测方法一般采用感烟、感温、感光探测器等进行探测。本文提出了一种嵌入式基于图像视觉特征的火灾检测方法,以TI公司的数字多媒体处理器TMS320DM642为核心,设计实现智能前端火灾探测与自动报警系统。通过DM642对视频图像进行采集并结合相应的智能图像处理与模式识别算法,对森林火险进行实时监控。实验结果表明,该系统比传统系统更进一步减少了误报率且具有响应快、监控范围广等优点。

ETC中具有车型识别功能的车辆检测器设计

介绍了专门用于ETC(不停车收费系统)中一种车辆检测器的软硬件设计方法。根据车辆检测器应用环境的特点给出了基准频率校正算法,可以对基准频率进行实时校正。并采用模糊模式识别算法进行车型识别。

基于模糊模式识别的车型分类研究

根据目前中国路桥车辆收费标准,提出了一种基于模糊模式识别的车型分类系统。车辆经过环形线圈传感器时,形成感应曲线,提取感应曲线的特征并进行特征分离,利用模糊模式识别方法对车型进行匹配分类。研究结果已在路桥收费系统以及交通流量统计中得到应用。

断陷湖盆缓坡带成藏模式研究

Halfgraben-like depressions have multiple layers of subtle traps, multiple coverings of oil-bearing series and multiple types of reservoirs. But these reservoirs have features of strong concealment and are difficult to explore. For this reason, many scholars contribute efforts to study the pool-forming mechanism for this kind of basins, and establish the basis for reservoir exploration and development. However, further study is needed. This paper takes HuiMin depression as an example to study the pool-forming model for the gentle slope belts of fault-depression lake basins. Applying multi-discipline theory, methods and technologies including sedimentary geology, structural geology, log geology, seismic geology, rock mechanics and fluid mechanics, and furthermore applying the dynamo-static data of oil reservoir and computer means in maximum limitation, this paper, qualitatively and quantitatively studies the depositional system, structural framework, structural evolution, structural lithofacies and tectonic stress field, as well as fluid potential field, sealing and opening properties of controlling-oil faults and reservoir prediction, finally presents a pool-forming model, and develops a series of methods and technologies suited to the reservoir prediction of the gentle slope belt. The results obtained in this paper richen the pool-forming theory of a complex oil-gas accumulative area in the gentle slope belt of a continental fault-depression basin. The research work begins with the study of geometric shape of fracture system, then the structural form, activity stages and time-space juxtaposition of faults with different level and different quality are investigated. On the basis of study of the burial history, subsidence history and structural evolution history, this paper synthesizes the studied results of deposition system, analyses the structural lithofacies of the gentle slope belt in the HuiMing Depression and its controlling roles to oil reservoir in the different structural lithofacies belts in time-space, and presents their evolution patterns. The study of structural stress field and fluid potential field indicates that the stress field has a great change from the Dong Ying stages to nowadays. One marked point among them is that the Dong Ying double peak- shaped nose structures usually were the favorable directional area for oil and gas migration, while the QuDi horst became favorable directional area since the GuanTao stage. Based on the active regular of fractures and the information of crude oil saturation pressure, this paper firstly demonstrates that the pool-forming stages of the LingNan field were prior to the stages of the QuDi field, whici provides new eyereach and thinking for hydrocarbon exploration in the gentle slope belt. The BeiQiao-RenFeng buried hill belt is a high value area with the maximum stress values from beginning to end, thus it is a favorable directional area for oil and gas migration. The opening and sealing properties of fractures are studied. The results obtained demonstrate their difference in the hydrocarbon pool formation. The seal abilities relate not only with the quality, direction and scale of normal stress, with the interface between the rocks of two sides of a fault and with the shale smear factor (SSF), but they relate also with the juxtaposition of fault motion stage and hydrocarbon migration. In the HuiMin gentle slope belt, the fault seal has difference both in different stages, and in different location and depth in the same stage. The seal extent also displays much difference. Therefore, the fault seal has time-space difference. On the basis of study of fault seal history, together with the obtained achievement of structural stress field and fluid potential field, it is discovered that for the pool-forming process of oil and gas in the studied area the fault seal of nowadays is better than that of the Ed and Ng stages, it plays an important role to determine the oil column height and hydrocarbon preservation. However, the fault seal of the Ed and Ng stages has an important influence for the distribution state of oil and gas. Because the influential parameters are complicated and undefined, we adopt SSF in the research work. It well reflects synthetic effect of each parameter which influences fault seal. On the basis of the above studies, three systems of hydrocarbon migration and accumulation, as well as a pool-forming model are established for the gentle slope belt of the HuiMin depression, which can be applied for the prediction of regular patterns of oil-gas migration. Under guidance of the pool-forming geological model for the HuiMin slope belt, and taking seismic facies technology, log constraint evolution technology, pattern recognition of multiple parameter reservoir and discrimination technology of oil-bearing ability, this paper develops a set of methods and technologies suited to oil reservoir prediction of the gentle slope belt. Good economic benefit has been obtained.

Reversed-phase high-performance liquid chromatographic investigation of urinary normal and modified nucleosides of cancer patients

Post-transcriptional modifications in RNA give rise to free modified ribonucleosides circulating in the blood stream and excreted in urine. Due to their abnormal levels in conjunction with several tumor diseases, they have been suggested as possible tumor markers. The developed RP-HPLC method has been applied to analyze the urinary nucleosides in 34 urinary samples from 15 kinds of cancer patients. The statistical analyses showed the urinary nucleoside excretion, especially modified nucleoside levels, in cancer patients were significantly higher than those in normal healthy volunteers. Factor analysis was used to classify the patients with cancer and normal healthy humans. It was found that using 15 urinary nucleoside levels or only five modified nucleoside levels as data vectors the factor analysis plot displayed two almost separate clusters representing each group. (C) 1999 Elsevier Science B.V. All rights reserved.

A Theory of Networks for Appxoimation and Learning

Learning an input-output mapping from a set of examples, of the type that many neural networks have been constructed to perform, can be regarded as synthesizing an approximation of a multi-dimensional function, that is solving the problem of hypersurface reconstruction. From this point of view, this form of learning is closely related to classical approximation techniques, such as generalized splines and regularization theory. This paper considers the problems of an exact representation and, in more detail, of the approximation of linear and nolinear mappings in terms of simpler functions of fewer variables. Kolmogorov's theorem concerning the representation of functions of several variables in terms of functions of one variable turns out to be almost irrelevant in the context of networks for learning. We develop a theoretical framework for approximation based on regularization techniques that leads to a class of three-layer networks that we call Generalized Radial Basis Functions (GRBF), since they are mathematically related to the well-known Radial Basis Functions, mainly used for strict interpolation tasks. GRBF networks are not only equivalent to generalized splines, but are also closely related to pattern recognition methods such as Parzen windows and potential functions and to several neural network algorithms, such as Kanerva's associative memory, backpropagation and Kohonen's topology preserving map. They also have an interesting interpretation in terms of prototypes that are synthesized and optimally combined during the learning stage. The paper introduces several extensions and applications of the technique and discusses intriguing analogies with neurobiological data.