快速构建目录树的算法研究

通常使用DFA和ITA算法构造目录树,本文分别对这两种算法进行了时间复杂性分析,16组实验结果表明DFA算法快于ITA算法。     

中国股票市场收益率的DFA分析

运用消除趋势波动分析方法,来分析我国上证综指、深证成指、青岛海尔、长安汽车的收盘指数的对数收益率序列．结果表明：从长期来看,前三者都存在持久性特征．上证综指的持久性特征要略强于深证成指,深证成指要强于青岛海尔,青岛海尔要强于长安汽车．但经过5次拟合后,发现前三者的指数值差异要大于长安汽车,即波动性要强于长安汽车．     

基于电子舌技术的不同品种大米区分识别研究

采用法国Alpha公司生产的Astree电子舌对四种不同品种大米进行区分识别研究,系统研究了大米样品经过不同预处理方法后的区分识别效果、研究味觉传感器优化前后大米样品区分效果、研究应用PCA、DFA两种模式识别方法区分识别效果;结果表明,大米经简单预处理后,电子舌能有效区分、识别出不同品种的大米。在大米品质检测方面,电子舌应用是一个新的检测方法,有着广阔的发展空间。     

对云量的长程相关性研究

为了探索云量的变化规律, 利用去趋势波动分析(DFA)方法, 选取北京、上海、太平洋西部和太平洋东部等4个区域, 对ISCCP每3小时的云量时间序列进行了分析, 发现: 这4个区域的云量在大的时间尺度上存在幂律相关性, 即云量具有较强的长程相关性(或持续性); 西太平洋上空云量的长程相关性强于东太平洋上空和其他两个地区。还发现海洋上折点出现的时间迟于陆地上。     

THE GRAMMATICAL COMPLEXITY AND SYMMETRY BREAKING OF SYMMETRICAL DYNAMICAL SYSTEMS

In this paper we discuss the grammatical complexity of dynamical systems,which satisfy antisymmetric condition and their iteratve interval can be divided into three monotone subintervals. A necessary and sufficient condition Jor the language determined by this system being regular language is proved.. Using the minimal DFA, symmetry breaking is analysed.     

DFA化简算法的一种改进方法

在深入研究DFA化简基本原理的基础上,首先给出现有分析算法（分割法）的形式化算法描述,然后证明了该算法存在着漏洞,并给出相应的解决方法。最后,借鉴时序逻辑门电路中原始状态表化简的方法,对现有分割算法进行修改,提出一种新的适用于任何DFA的化简算法——K次划分法。     

面向品牌认知的产品形态推演方法

指出了体验经济时期品牌识别对于企业经营的重要性以及产品系列延伸策略的普遍性。针对品牌视觉认知,采用Design Formation Analysis(DFA)方法提取品牌识别的形态隐式和显式特征。在此基础上提出了基于形态推演法则的形状文法,并通过此进行产品形态推演。最后通过吸油烟机形态推演实例验证了方法的可行性。     

The effect of sequential dual-gas testing on laser-induced breakdown spectroscopy-based discrimination: Application to brass samples and bacterial strains

Four Cu–Zn brass alloys with different stoichiometries and compositions have been analyzed by laser-induced breakdown spectroscopy (LIBS) using nanosecond laser pulses. The intensities of 15 emission lines of copper, zinc, lead, carbon, and aluminum (as well as the environmental contaminants sodium and calcium) were normalized and analyzed with a discriminant function analysis (DFA) to rapidly categorize the samples by alloy. The alloys were tested sequentially in two different noble gases (argon and helium) to enhance discrimination between them. When emission intensities from samples tested sequentially in both gases were combined to form a single 30-spectral line “fingerprint” of the alloy, an overall 100% correct identification was achieved. This was a modest improvement over using emission intensities acquired in argon gas alone. A similar study was performed to demonstrate an enhanced discrimination between two strains of Escherichia coli (a Gram-negative bacterium) and a Gram-positive bacterium. When emission intensities from bacteria sequentially ablated in two different gas environments were combined, the DFA achieved a 100% categorization accuracy. This result showed the benefit of sequentially testing highly similar samples in two different ambient gases to enhance discrimination between the samples.     

DCCA cross-correlation coefficient apply in time series of air temperature and air relative humidity

In this paper we propose, analyze and also quantify cross-correlations between climatological data. For this purpose we adopt the DCCA cross-correlation coefficient ρ_DCCA. In order to accomplish this goal, we calculate the cross-correlation between time series of air temperature and relative humidity. This analysis was performed taking into account several stations (cities) around the world. The results found here, depending on the station location, may exhibit one of the following behaviors, i.e., negative, positive, or null cross-correlations. It is noteworthy that, the level of cross-correlation between air temperature and relative humidity is quantified in these cases. Finally, DCCA cross-correlation coefficients show that, in general, the data are influenced by seasonal components.     

Limb dominance changes in walking evolution explored by asymmetric correlations in gait dynamics

Fluctuations in the stride interval time series of unconstrained walking are not random but seem to exhibit long-range correlations that decay as a power law (Hausdorff et al. (1995) [35]). Here, we examine whether asymmetries are present in the long-range correlations of different gait parameters (stride, swing and stance intervals) for the left and right limbs. Gait dynamics corresponding to 16 healthy subjects were obtained from the Physionet database, which contains stride, stance and swing intervals for both left and right limbs. Detrended Fluctuation Analysis (DFA) revealed the presence of asymmetric long-range correlations in all gait cycle variables investigated. A rich variety of scaling exponent dynamics was found, with the presence of synchronicity, decreased correlations and dominant correlations. The results are discussed in terms of the hypothesis that reduced strength of long-range correlations reflect both enhanced stability and adaptability.