嵌入式GPS／GIS系统设计的几个关键问题及解决方法

提出嵌入式GPS/GIS系统设计中的几个关键技术问题并给出解决方案。对GPS数据质量采用神经元辨识的方法进行控制;对大数据量底图数据采用一种新的地图综合方法建立多级显示机制,节省内存,提高图形显示效率;建立基于la-bel的空间算子实现方式,完成采集图斑的现场变更,减少内业数据处理的工作量。实际应用表明,这些方法能够满足嵌入式GPS/GIS系统应用于土地调查业务的需要,提高了调查效率。     

多特征融合的蛋白质相互作用位点预测

蛋白质相互作用位点预测为蛋白质功能和药物设计的理解提供重要线索。而蛋白质的各种特征为蛋白质相互作用位点预测提供了大量有用信息,特别是进化信息、残基序列邻近和空间邻近性。不同的蛋白质特征对蛋白质间的相互作用的贡献也不一样。通过提取蛋白质序列谱、保守性和残基熵,提出了特征融合技术对蛋白质相互作用位点进行研究,采用SVM构建三种预测器,分别对各种不同的特征加以验证,实验结果表明了基于特征融合方法的有效性和正确性。     

基于贝叶斯网络的博弈融合建模

针对多源信息冲突环境下的信息融合问题,提出了一种博弈融合模型,并根据Bayes网络推理理论与信息论交互熵等定义给出了此博弈融合模型的具体算法,最后对此算法进行了仿真,根据实验结果进行了分析与总结。     

基于某微型飞行器的2种图像导航算法性能比较

导航系统是微型飞行器中必不可少的重要部分,在城市、建筑物内部或强电磁干扰等环境下,要实现导航必须采用全新的技术。图像导航是其有效技术之一。根据微型飞行器导航系统实时性和算法精准性的要求,研究了2种图像导航算法：互相关匹配法和局部熵差法。为了降低计算量,使其易于工程实现,采用了分层搜索等技术,并对2种算法进行了改进。仿真结果表明：“互相关匹配法”更适合微型飞行器的图像导航。     

离散混沌系统类随机性的符号熵分析法

采用符号熵分析法,分析和讨论了经典的Logistic映射和Henon映射的类随机性强弱.先将离散混沌系统产生的实数序列转化为二进制序列,然后进行编码,计算其符号熵,绘制其符号熵图,并深入讨论了系统参数和初始值对符号熵的影响.数值仿真分析表明,符号熵法能定量区别不同离散混沌系统类随机性的强弱.同时作为随机源,Logistic映射比Henon映射好.     

Topological entropy and data rate for practical stability: a scalar case

A special class of nonlinear systems, i.e. expanding piecewise affine discrete‐time scalar systems with limited data rate, is used to investigate the role of topological entropy and date rate in a practical stability problem. This special class of nonlinear system as an abstract model is an extension of discrete‐time unstable scalar systems, a well‐known model for quantized feedback design. For such systems with finite quantization levels, how to design a quantized feedback controller to achieve practical stability is considered as a boundability problem. Unlike the existing results about topological entropy for nonlinear stabilization and optimal control for linear systems, for the boundability problem under consideration, the feedback topological entropy defined in this paper is not equal to the minimum number of the quantization interval (i.e. the minimal information rate) and only provides a necessary condition for the boundability of our system under some condition. A necessary and sufficient condition for the boundability is also presented in terms of an inequality related to data rate and the minimum number of quantization intervals. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Application of maximum entropy principle for reliability-based design optimization

The maximum entropy principle (MEP) is used to generate a natural probability distribution among the many possible that have the same moment conditions. The MEP can accommodate higher order moment information and therefore facilitate a higher quality PDF model. The performance of the MEP for PDF estimation is studied by using more than four moments. For the case with four moments, the results are compared with those by the Pearson system. It is observed that as accommodating higher order moment, the estimated PDF converges to the original one. A sensitivity analysis formulation of the failure probability based on the MEP is derived for reliability-based design optimization (RBDO) and the accuracy is compared with that by finite difference method (FDM). Two RBDO examples including a realistic three-dimensional wing design are solved by using the derived sensitivity formula and the MEP-based moment method. The results are compared with other methods such as TR-SQP, FAMM + Pearson system, FFMM + Pearson system in terms of accuracy and efficiency. It is also shown that an improvement in the accuracy by including more moment terms can increase numerical efficiency of optimization for the three-dimensional wing design. The moment method equipped with the MEP is found flexible and well adoptable for reliability analysis and design.     

基于二维小波变换的车牌边缘检测的研究

在Matlab环境下运用基于二维小波变换边缘检测方法提取车牌信息的边缘。实验证明这种方法对车牌边缘信息提取的效果比传统的边缘提取算子提取车牌信息边缘的效果要好,特别是对伪边缘和图片噪声的过滤作用比较明显。     

信息系统属性约简的比较研究

属性约简是粗糙集理论研究的核心问题之一。利用信息熵定义了信息系统的熵约简,从代数与信息熵两种不同角度出发对属性约简进行讨论。通过比较分析,分别在信息系统、协调与不协调决策表中得到这两种观点下属性约简的一些等价关系和蕴含关系,揭示了不同意义下属性约简的本质联系。     

一种基于脉冲耦合神经网络的语音情感识别新方法

针对汉语语音情感识别问题,提出了一种基于脉冲耦合神经网络(PCNN)的识别方法。该方法将语音转化为语谱图后输入到PCNN,得到输出图像的神经元点火序列及其熵序列作为语音情感的特征,利用其特征实现语音情感识别。实验结果表明,该方法可以有效地识别“高兴”与“平常”这两种不同的情感。该方法将PCNN引入到语音情感识别的应用研究中,开拓了语音和图像信号结合处理的新领域,同时对于PCNN的理论研究和实际应用具有重要的现实意义。