合成孔径雷达最优量化编码器

合成孔径雷达ＳＡＲ数据率高、数据量大，对ＳＡＲ原始数据的压缩可以降低对数传和数据存储的要求。文中用ＳＢＡＳＡＰ－ＳＡＲ原始数据对合成孔径雷达信号统计模型进行了研究，提出了一种２ｂｉｔ自适应量化编码方法，并用ＳＥＡＳＡＴ—ＳＡＲ原始数据进行了编－译码实验，获得了该２ｂｉｔ量化编码器的性能指标测试结果。     

赵爽的《勾股园方图》研究

本文讨论了赵爽《勾股园方图》中的图形,提出了新的设想,用此设想验证了全部命题,并且对《中国数学史》中的两点解释也提出了不同的看法。     

合成孔径雷达图像特征及压缩研究

合成孔径雷达图像压缩有助于减少数据率，对图像传输和存贮效率的提高有积极的意义。对合成孔径雷达图像统计模型进行了研究，给出了其概率分布和相关性能分析，并用ＳＥＡＳＡＴ－ＳＡＲ数据进行了统计。据此提出了无失真压缩算法，达到了熵压缩边界，并对合成孔径雷达有失真压缩进行了讨论。     

从《伪币制造者》解读纪德小说遗产

法国小说家纪德的《伪币制造者》以独特的叙述手法著称于世。本文则想重新探讨这篇小说,研究在十九世纪末二十世纪初现实主义小说出现合法性危机时,其如何以多角度网状叙事、思想小说、百科全书的形式解决了这一危机,拓展了小说的空间,并为未来小说样貌留下了一笔特殊的遗产。     

有限元网格质量和材料黏度模型对注塑件翘曲分析的影响

利用Moldflow分析了吸尘器轴承座的成型过程,通过细化构件的有限元网格和对比网格质量,检验了有限元分 析结果收敛性,确认需要结合网格质量来改进计算过程。构件变形的有限元分析结果与实测数据进行比较,在最大翘曲 的估计方面效果较好,显示了对注塑过程和构件进行精确分析的重要性。文中也尝试采用不同的黏度模型对注塑件翘 曲进行分析,保证分析方法的一致和完整,为基于有限元分析的模具设计和加工过程优化积累经验。     

数据挖掘中属性项压缩的统计方法研究

文章试图将统计思想与(Rough)粗糙集理论相结合,针对事务性数据库属性项压缩问题提出了一些行之有效的方法,即基于重要性的属性压缩、基于相依性的属性压缩、属性项的广义线形分析及压缩、基于多重相关性的属性项压缩,以此达到数据库压缩之目的。     

试析卡夫卡小说父子冲突的审美三角结构

在卡夫卡的创作生涯中,父子冲突是一个无法调和的悖论性命题,这个命题作为西方传统文化母题,蕴含了丰富的哲学和历史文化内涵。考察卡夫卡的日常生活和写作生活,发现这两种生活形成一种矛盾结构,类似于西方文化语境中的父子冲突。用拉康的审美三角结构理论去分析这个大的父子冲突结构,可以发现这个结构内部蕴含的审美张力。     

Estimation for u-shaped beta distributions: minimum hellinger distance and related methods

We compare minimum Hellinger distance and minimum Heiiinger disparity estimates for U-shaped beta distributions. Given suitable density estimates, both methods are known to be asymptotically efficient when the data come from the assumed model family, and robust to small perturbations from the model family. Most implementations use kernel density estimates, which may not be appropriate for U-shaped distributions. We compare fixed binwidth histograms, percentile mesh histograms, and averaged shifted histograms. Minimum disparity estimates are less sensitive to the choice of density estimate than are minimum distance estimates, and the percentile mesh histogram gives the best results for both minimum distance and minimum disparity estimates. Minimum distance estimates are biased and a bias-corrected method is proposed. Minimum disparity estimates and bias-corrected minimum distance estimates are comparable to maximum likelihood estimates when the model holds, and give better results than either method of moments or maximum likelihood when the data are discretized or contaminated, Although our re¬sults are for the beta density, the implementations are easily modified for other U-shaped distributions such as the Dirkhlet or normal generated distribution.     

比较视角的西三角城市群综合发展水平测度

选取六项大类指标将西三角城市群与我国三大城市群综合发展水平进行比较,结果表明,西三角城市群虽从地理角度构成了城市群形态,但发展还不成熟,缺乏应有的系统效应。加快发展西三角城市群,应加快城市群交通网络系统建设,重视政府宏观调控,优先发展旅游业和物流服务业。     

Sparse Markov Chains for Sequence Data

Finite memory sources and variable‐length Markov chains have recently gained popularity in data compression and mining, in particular, for applications in bioinformatics and language modelling. Here, we consider denser data compression and prediction with a family of sparse Bayesian predictive models for Markov chains in finite state spaces. Our approach lumps transition probabilities into classes composed of invariant probabilities, such that the resulting models need not have a hierarchical structure as in context tree‐based approaches. This can lead to a substantially higher rate of data compression, and such non‐hierarchical sparse models can be motivated for instance by data dependence structures existing in the bioinformatics context. We describe a Bayesian inference algorithm for learning sparse Markov models through clustering of transition probabilities. Experiments with DNA sequence and protein data show that our approach is competitive in both prediction and classification when compared with several alternative methods on the basis of variable memory length.