基于自动机原理的自动售货机软件的实现

利用自动机原理对现有的自动售货机的工作模式进行了分析，指出了自动售货机在购买多种商品时的不方便之处和销售管理上的落后现象，提出了用软件方法对自动售货机工作模式进行优化和扩展，并增强其管理功能，以使自动化销售过程更快捷、准确和有效。     

网络入侵检测中多模式匹配的状态编码方法

为了减少网络入侵检测系统的硬件实现方案中自动机占用的存储容量,提出了一种自动机状态的编码方法。该方法通过对自动机状态重新进行编号,使得多个状态能够用一个通配编号来表示,这样自动机中具有相同输入和下一状态的多条变迁就能被聚合为一条,大大减小了需要存储的变迁数目。可以证明状态编码方法能够将变迁数目减小到理论上最小值同时保证自动机恒定的处理速率。实验表明,对于常见特征串集,该方法可以将变迁数目减小98.9%以上。     

A 21st century technique for food control: Electronic noses

This work examines the main features of modern electronic noses (e-noses) and their most important applications in food control in this new century. The three components of an electronic nose (sample handling system, detection system, and data processing system) are described. Special attention is devoted to the promising mass spectrometry based e-noses, due to their advantages over the more classical gas sensors. Applications described include process monitoring, shelf-life investigation, freshness evaluation, authenticity assessment, as well as other general aspects of the utilization of electronic noses in food control. Finally, some interesting remarks concerning the strengths and weaknesses of electronic noses in food control are also mentioned.     

兰村站天然径流演变长程相关性分析

采用非趋势波动分析法（DFA）对汾河上游兰村站45年的天然月径流量进行了长程相关性分析,并计算出了标度指数。结果表明汾河上游径流演变具有正长程相关性,汾河上游历史径流量的演变呈衰减趋势状态基本保持一致,并会在未来的演变中继续保持这种衰减趋势状态的变化规律。     

DCCA cross-correlation coefficient differentiation: Theoretical and practical approaches

We propose in this paper to establish a well-defined relationship between _αDFA${\alpha }_{DFA}$ (the long range auto-correlation exponent) and _λDCCA${\lambda }_{DCCA}$ (the long range cross-correlation exponent), respectively described by the DFA and DCCA methods. This relationship will be accomplished theoretically by differentiating the DCCA cross-correlation coefficient, _ρDCCA(n)${\rho }_{DCCA}\left(n\right)$. Also, for some specific times series, we apply this theory in order to establish its validity.     

有限自动机在密码技术中的应用探讨

通过对流密码体制一般原理的分析,提出了一个基于DFA的流密码模型.依据该模型,可以构造一类初始密钥长度可变、加密/解密简单快捷、强度较高的流密码,以满足不同的应用需求.     

产险公司资产负债管理的DFA方法实证分析

介绍了动态财务分析(DFA)这一主要适用于产险公司的资产负债管理工具.该工具运用Monte Carlo模拟方法在一系列不同情境下产生保险公司整体的财务结果.本文利用公共的DFA模型和中国市场上的实际数据参数化模型,建立起在中国市场上适用的DFA模型.在模拟过程中可以看出,DFA将外部环境等因素考虑进来,符合经营环境多变的情形;管理层可借由DFA模拟出的大量财务数据对公司经营状况进行分析,预测公司在未来几年中的财务进展状况,并由情景测试的方法来展示如何通过改变公司经营策略改善公司的经营状况及资产配置等.借助DFA模型可达到资产负债管理的目的,显示出其作为资产负债管理工具的巨大优势.     

Recognition of benzene, toluene and xylene using TGS array integrated with linear and non-linear classifier

Three volatile organic compounds (VOCs): benzene, toluene and xylene were measured with an array of six Taguchi gas sensors in the air with variable humidity content. The recognition of single compounds was performed, based on measurement results. The principal component analysis (PCA) pointed at humidity as the main classification factor in the measurement data set. The linear discriminant analysis (LDA) was applied to overcome this drawback and enforce classification with respect to benzene, toluene or xylene. It was shown that discriminant function analysis (DFA), which is an LDA method allowed for 100% success rate in test samples recognition of benzene. It did not allow for accurate recognition of test samples of toluene or xylene. Following, the non-linear classifier, radial basis function neural network (RBFNN) was applied. A specific configuration of input ‘s was found, which provided for successful recognition of each single compound: benzene, toluene or xylene in air with variable humidity content.     

中国股票市场的长记忆性与市场发展状态

对于中国股市的长记忆性问题,许多的学者得到了不同的结论,这主要是由于不同方法自身存在着缺陷,针对这一问题,分别运用经典R/S分析,修正R/S分析,DFA及广义Hurst指数等统计分析方法对其进行实证研究,以期使结果更加稳健.结果发现沪深两市均具有长记忆性特征.此外,研究了广义Hurst指数值与市场发展状态之间的依赖性,并根据该性质得到结论认为沪深两市属于新兴的、非有效的市场.     

基于DFA的股价指数自相关分析

以股价指数的自相关函数为时间序列,运用非趋势波动分析DFA方法研究我国股票市场的长期相关性,结果表明,上海股票市场和深圳股票市场在跨时间尺度的股价指数之间存在着相关性,呈现为持久性的时间序列,随机游走不再适用,股价指数的有偏随机游走是当下投资者对信息反应生成的,由于市场信息不具有同质等量分布,造成交锗 对信息理解的差异,信息不能瞬间或及时反映到股票价格中,存在着复杂滞后交易,导致了股价指数的有偏随机游走。