RLL码的计算机辅助设计

本文着重讨论计算机辅助设计RLL码的具体实现问题.该过程首先根据RLL码两个参数d,k确定一个编码率p/q,然后构造出RLL码的高阶状态转换-输出符号矩阵并求相应的近似特征向量.最后通过状态分裂和状态归并过程,即可得到一个满足d,k约束的编码输出表.其中状态转换-输出符号矩阵为实现计算机辅助设计RLL码提供了有效的数据结构,而且要优化RLL码编码器,就必须有选择地进行状态分裂.     

数字测图,数字制图及勘测设计一体化

简述引用瑞得软件建立数字化成图系统，以进一步实现测量与工程设计一体化，使得繁琐的作业过程变为简单，缩短作业时间，不断提高生产作业效率。     

制作矢量轮廓字库

本文介绍了一种如何从常见的点阵字库制作矢量轮廓字库的算法。算法采用了预处理、轮廓跟踪和轮廓逼近这三个主要步骤来制作每一个矢量文字，然后采用一种２字节的索引结构加以存储。     

用线性状态观测器重构交流矢量控制系统中的负载扰动

在异步电动机磁场定向数学模型的基础上,给出了恒磁条件下异步电动机的解耦模型及传动系统的线性状态方程,并提出了重构负载扰动转矩的线性状态观测器。利用重构的负载转矩在矢量控制系统中进行扰动前馈,明显地提高了系统的抗负载扰动能力,从而为进一步提高矢量控制系统的动态性能开辟了一条有效的途径。     

一种新型微处理器功能验证

文中介绍一种新型微处理器的验证方法，并对相关的一些验证策略进行深入的讨论。     

变频驱动在长运距带式输送机系统的应用

介绍了赵庄煤矿主斜井长运距带式输送机系统的构成,通过变频器在输送系统上的应用实践,表明该变频驱动技术具有先进性。     

水利测绘产品质量分析与检验方法研究

分析了影响测绘产品质量的主要因素，提出了完善测绘市场、加强水电测绘产品的检查验收是保证产品质量的关键，同时提出了产品质量的等级划分和检验方法，并且说明了根据测量工作的不同要求对检验方法及检验深度合理定位的必要性。     

Achievement of specificational information usage with true and false feedback in learning a visual relative-mass discrimination task.

Participants' usage of informational variables in learning visual relative-mass discrimination in collisions was tracked by means of PROBIT correlations. Four groups received feedback that was true or accorded with either of three nonspecificational cue variables. A majority in each group adopted the feedback, but several participants defied the false feedback. Unlike in previous research, the fit to data of the relative-mass invariant could not be bettered by post hoc linear combinations of the cues. Discriminability was lower in the use of the invariant. Analytic complexity was rejected as an explanation for discriminability differences. A "smart mechanism" for pickup of the relative-mass invariant was developed as an extension of G. Johansson's (1950/1994) vector model. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Two-tier architecture for unconstrained handwritten character recognition

In this paper, we propose an approach that combines the unsupervised and supervised learning techniques for unconstrained handwritten numeral recognition. This approach uses the Kohonen self-organizing neural network for data classification in the first stage and the learning vector quantization (LVQ) model in the second stage to improve classification accuracy. The combined architecture performs better than the Kohonen self-organizing map alone. In the proposed approach, the collection of centroids at different phases of training plays a vital role in the performance of the recognition system. Four experiments have been conducted and experimental results show that the collection of centroids in the middle of the training gives high performance in terms of speed and accuracy. The systems developed also resolve the confusion between handwritten numerals.     

用于一维图像识别的支撑矢量机方法

研究了支撑矢量机的分类机理,并利用支撑矢量机对雷达目标一维像进行了识别.识别的结果表明了该方法的优越性,并显示它可以对残缺不全的样本进行识别.