基于连通域的模板匹配法用于字符识别的算法研究

文章介绍了一种用于字符识别的基于连通域的模板匹配算法.该算法是在传统的模板匹配法的基础上,运用了重心重叠等处理方法,并且对字符块进行连通域处理后再实施匹配,最后利用最大相似法得出识别结果.该算法在光学仪器读数图象的动态识别中取得了良好的识别效果.     

Block-based neural networks

This paper presents a novel block-based neural network (BBNN) model and the optimization of its structure and weights based on a genetic algorithm. The architecture of the BBNN consists of a 2D array of fundamental blocks with four variable input/output nodes and connection weights. Each block can have one of four different internal configurations depending on the structure settings, The BBNN model includes some restrictions such as 2D array and integer weights in order to allow easier implementation with reconfigurable hardware such as field programmable logic arrays (FPGA). The structure and weights of the BBNN are encoded with bit strings which correspond to the configuration bits of FPGA. The configuration bits are optimized globally using a genetic algorithm with 2D encoding and modified genetic operators. Simulations show that the optimized BBNN can solve engineering problems such as pattern classification and mobile robot control.     

PLC在高浓度冲稀自动控制系统的应用

本文在介绍高浓度冲稀自动控制系统的工作原理、特点、系统调校及日常维护要点的基础上,探讨了PLC在这种类型的系统中的应用。     

一个基于CORBA和Java技术的分布式并行有限元计算环境

该文结合ＣＯＲＢＡ（Ｃｏｍｍｏｎ Ｏｂｊｅｃｔ Ｂｒｏｋｅｒ Ａｒｃｈｉｔｅｃｔｕｒｅ）和Ｊａｖａ技术,提出了一个能在支持ＴＣＰ／ＩＰ协议的异构网络环境下实现分布式有限元计算环境的具体方案,为了验证方案的可行性,在西南交通大学应用力学与工程系计算中心的局域网上实现了分布式并行计算环境的基本框架,并进行了１０００阶矩阵相乘的计算。     

MATLAB 7.3与.NET新接口技术

MATLAB r2006(7.3)下利用COM组件实现VB.net与MATLAB混合编程的新方法。并用实例介绍了这种方法的具体应用过程。     

Rosetta: semantic support for model-centered systems-level design

With the advent of system-on-chip (SoC) technology, the design of small electrical systems has become a systems engineering task. Such tasks require working at high levels of abstraction to build systems by either integrating information from various design domains or modeling different aspects of the same component. Designers of traditional computer-based systems usually rely on component-based techniques that parallel the physical architecture. The model-based approach encompasses the component-centered approach, treating structural decomposition as a single model in the overall hierarchy. Model-centered semantics and languages let designers concentrate on the data, computation, or communication models that describe complex computer-based SoC requirements. Appropriate design semantics specify each system aspect, and the designer assembles those aspects into models to define complete systems and components. The developers of Rosetta, a heterogeneous systems-level modeling language that supports predictive design analysis, have identified mechanisms for defining and composing models that specify multiple domains of interest from many perspectives. Rosetta requirements and domains define test cases and generate abstract vectors for each test scenario. Several analysis tools are under development for transforming Rosetta into existing analysis environments, and the authors describe their authors are also developing native analysis tools for symbolic verification and simulation environments. The authors use Rosetta to provide computation models for customized digital and mixed-signal system-specification environments. Other domains to support, optical and microelectrical mechanical systems specifications are under consideration     

Multidimensional local spatial autocorrelation measure for integrating spatial and spectral information in hyperspectral image band selection

Hyperspectral band selection aims at the determination of an optimal subset of spectral bands for dimensionality reduction without loss of discriminability. Many conventional band selection approaches depend on the concept of “statistical distance” measure between the probability distributions characterizing sample classes. However, the maximization of separability does not necessarily guarantee that a classification process results in the best classification accuracies. This paper presents a multidimensional local spatial autocorrelation (MLSA) measure that quantifies the spatial autocorrelation of the hyperspectral image data. Based on the proposed spatial measure, a collaborative band selection strategy is developed that combines both spectral separability measure and spatial homogeneity measure for hyperspectral band selection without losing the spectral details useful in classification processes. The selected band subset by the proposed method shows both larger separability between classes and stronger spatial similarity within class. Case studies in biomedical and remote sensing applications demonstrate that the MLSA-based band selection approach improves object classification accuracies in hyperspectral imaging compared with conventional approaches.     

IrisCode decompression based on the dependence between its bit pairs

IrisCode is an iris recognition algorithm developed in 1993 and continuously improved by Daugman. Understanding IrisCode's properties is extremely important because over 60 million people have been mathematically enrolled by the algorithm. In this paper, IrisCode is proved to be a compression algorithm, which is to say its templates are compressed iris images. In our experiments, the compression ratio of these images is 1:655. An algorithm is designed to perform this decompression by exploiting a graph composed of the bit pairs in IrisCode, prior knowledge from iris image databases, and the theoretical results. To remove artifacts, two postprocessing techniques that carry out optimization in the Fourier domain are developed. Decompressed iris images obtained from two public iris image databases are evaluated by visual comparison, two objective image quality assessment metrics, and eight iris recognition methods. The experimental results show that the decompressed iris images retain iris texture that their quality is roughly equivalent to a JPEG quality factor of 10 and that the iris recognition methods can match the original images with the decompressed images. This paper also discusses the impacts of these theoretical and experimental findings on privacy and security.     

努尔加水库台阶式溢洪道水力特性的研究

本文主要介绍努尔加水库台阶式溢洪道的试验研究成果。通过模型试验,对单宽流量在24.17—118m3/s.m的台阶式溢洪道的台阶坡度,高度和水力特性认识更加深入。试验表明坡度较陡,单宽流量较小的情况下消能效果最好。研究工作对大单宽流量台阶溢洪道的推广应用具有较高的参考价值。     

基于PXA270的分布式地铁车载系统开发

基于PXA270硬件平台与WinCE嵌入式操作系统,采用媒体文件的IP组播传输、DirectShow数据解码播放、报站信息的无线射频自动触发技术,实现列车终端报站、多媒体播放和信息提示等功能,同时可以实现车头与车厢间的车载广播中心和车载播放终端功能互换,增加了车载系统的可靠性和灵活性。