基于目标轮廓几何特征的电容元件定位方法

随着印刷电路板(PCB)生产工艺愈加复杂,电容元件的定位识别难度也随之增加。在实际生产中,为了节约成本、减少出错率,需要在焊接之前对电路板进行检测,同时为了固定电路板上元器件,一般会使用压板固定电路板。针对此种情况,提出一种复杂背景下被遮盖电容元件的定位方法,通过对采集到的PCB图像进行预处理、阈值分割、边缘提取和Harris角点检测等操作,进而根据电容元件目标轮廓的几何特征对元件进行定位。该方法已经在实践中得到应用,定位准确率高、速度快,能广泛应用于实际生产中。     

面向中文专利文献的有标记并列结构的统计分析

该文在中文专利语料的基础上,统计分析了中文专利文献中有标记并列结构的内部特征和外部特征。内部特征主要考察了中文专利文献中有标记并列结构的并列标记、并列结构内部分析和词性分布等。外部特征主要统计了可能的边界特征词,并分析了有标记并列结构在中文专利文献中出现的外部环境。     

距离法求语言特征主成分

语言特征成分的数量决定了成分对语言特征的影响度.作者把影响度视作距离,建立了一个数学模型,通过距离判断来求取语言特征主成分.     

低层特征融合的图像检索算法设计

现阶段基于单一的特征提取算法已不能满足人们对图像查准率、查全率的要求。有效地整合图像的颜色、纹理、形状等特征,使得各特征优势互补,进而提高系统检索效率现已成为一个值得研究并深入的课题[1]。从颜色、纹理两方面的特征出发,研究并设计了一整套的方案,很好的解决了查准率、查全率等问题。     

南水北调中线小南河串流片防洪水位计算

传统的多河流串流计算主要采用水库联调的方法,把串流的各条河流概化为静态水库,库水位水平且不考虑横向流动。为解决串流区水流的横向流动及水面线并不总像库水位一样水平的问题,采用二维非恒定流数学模型计算串流区洪水演进。通过概化地形、考虑入流、糙率、边界条件和水流的横向流动等因素,计算出了整个串流区域的水面线、水深、流速、出流等水力要素,并给出洪水演进模拟图,为确定河流与总干渠交叉建筑物的规模、总干渠左岸沿线水面线和对沿线村庄、农田的防洪影响提供了可靠的依据。     

Multi-class supervised classification of electrical borehole wall images using texture features

Electrical borehole wall images represent micro-resistivity measurements at the borehole wall. The lithology reconstruction is often based on visual interpretation done by geologists. This analysis is very time-consuming and subjective. Different geologists may interpret the data differently. In this work, linear discriminant analysis (LDA) in combination with texture features is used for an automated lithology reconstruction of ODP (Ocean Drilling Program) borehole 1203A drilled during Leg 197. Six rock groups are identified by their textural properties in resistivity data obtained by a Formation MircoScanner (FMS). Although discriminant analysis can be used for multi-class classification, non-optimal decision criteria for certain groups could emerge. For this reason, we use a combination of 2-class (binary) classifiers to increase the overall classification accuracy. The generalization ability of the combined classifiers is evaluated and optimized on a testing dataset where a classification rate of more than 80% for each of the six rock groups is achieved. The combined, trained classifiers are then applied on the whole dataset obtaining a statistical reconstruction of the logged formation. Compared to a single multi-class classifier the combined binary classifiers show better classification results for certain rock groups and more stable results in larger intervals of equal rock type.     

一种无接触供电的无线鼠标

介绍了一种无接触供电的无线鼠标设计电路,无接触电能发射装置采用USB供电,通过自激振荡电路产生了138 kHz的高频振荡电压;无接触电能接收装置采用感应耦合方式获取电能.无线鼠标用无线模块nRF24E1构成信号发射和接收电路,该电路除具备有线鼠标全部功能外,还可以离开电脑远距离灵活操纵鼠标.     

铁路无线列调系统的功能运用分析

列车无线调度通信系统,简称无线列调,是铁路无线通信的主要组成部分,是组织铁路运输、保障行车安全、提高生产效率的重要通信设施,其通信质量的好坏直接关系到铁路的行车安全。本论文主要介绍无线通信的特点和我国无线列调通信系统的现状、构成、作用、功能、制式及工作频率,同时提出本文研究的意义和文章组成。     

Fuzzy ARTMAP classification of invariant features derived using angle of rotation from a neural network

Conventional regular moment functions have been proposed as pattern sensitive features in image classification and recognition applications. But conventional regular moments are only invariant to translation, rotation and equal scaling. It is shown that the conventional regular moment invariants remain no longer invariant when the image is scaled unequally in the x- and y-axis directions. We address this problem by presenting a technique to make the regular moment functions invariant to unequal scaling. However, the technique produces a set of features that are only invariant to translation, unequal/equal scaling and reflection. They are not invariant to rotation. To make them invariant to rotation, moments are calculated with respect to the principal axis of the image. To perform this, the exact angle of rotation must be known. But the method of using the second-order moments to determine this angle will also be inclusive of an undesired tilt angle. Therefore, in order to correctly determine the amount of rotation, the tilt angle which differs for different scaling factors in the x- and y-axis directions for the particular image must be obtained. In order to solve this problem, a neural network using the back-propagation learning algorithm is trained to estimate the tilt angle of the image and from this the amount of rotation for the image can be determined. Next, the new moments are derived and a Fuzzy ARTMAP network is used to classify these images into their respective classes. Sets of experiments involving images rotated and scaled unequally in the x- and y-axis directions are carried out to demonstrate the validity of the proposed technique.     

连续属性离散化算法SHD及其改进

为了让规则抽取算法能更好地适用于连续属性领域的问题,文章提出了一种有导师的连续属性离散化算法ＳＨＤ,并将该算法扩展到多连续属性处理领域。在此基础上,文章对该算法的数据预处理过程进行了探讨,提出了一种基于类间离散度矩阵分析属性空间重构造算法,并将其应用到属性预处理过程中。算法测试证明,对于连续属性领域的问题,使用ＳＨＤ属性离散化算法将明显改进后继规则抽取算法的效果。