Process capability analysis and estimation scheme for autocorrelated data

<正>Autocorrelation is prevalent in continuous production processes,such as the processes in the chemical and pharmaceutical industries.With the development of measurement technology and data acquisition technology,sampling frequency is getting higher and the existence of autocorrelation cannot be ignored.This paper analyzes five estimation schemes of process capability for autocorrelated data.Comparisons among these schemes are discussed for small sample and large sample.In conclusion,this paper gives a procedure of process capability analysis for autocorrelated data.     

Clustering patents using non-exhaustive overlaps

Patent documents are unique external sources of information that reveal the core technology underlying new inventions.Patents also serve as a strategic data source that can be mined to discover state-of-the-art technical development and subsequently help guide R&D investments.This research incorporates an ontology schema to extract and represent patent concepts.A clustering algorithm with non-exhaustive overlaps is proposed to overcome deficiencies with exhaustive clustering methods used in patent mining and technology discovery.The non-exhaustive clustering approach allows for the clustering of patent documents with overlapping technical findings and claims,a feature that enables the grouping of patents that define related key innovations.Legal advisors can use this approach to study potential cases of patent infringement or devise strategies to avoid litigation.The case study demonstrates the use of non-exhaustive overlaps algorithm by clustering US and Japan radio frequency identification (RFID) patents and by analyzing the legal implications of automated discovery of patent infringement.     

Connecting informal networks to management of tacit knowledge

The relationship between tacit knowledge and informal networks has not been fully explored.Tacit knowledge cannot be well managed directly,because it is deeply embedded in individual actions and experiences.This study proposes an approach to managing informal networks as a new middle way to facilitate the sharing and transferring of tacit knowledge,owing to the fact that tacit knowledge is mostly shared and transferred through informal networks.To support the idea of the approach,an empirical case study of applying the approach to management of a large scientific project is also included.Our findings suggest that informal networks play essential roles for management of tacit knowledge,and thus good management of informal networks can lead to efficient sharing and transferring of tacit knowledge.     

一种新型神经网络控制器的研究

提出了一种新型神经网络控制器,其控制机理与PID控制相类似,但解决了常规PID控制存在的快速性与超调量的矛盾.给出了该神经网络控制器的自适应学习算法,分析讨论了控制系统的稳定性.仿真实验表明,这种新型神经网络控制器构成的自适应控制系统具有较强的适应性和鲁棒性.     

一种SAR图像目标识别方法

提出了一种新的合成孔径雷达 (SAR)图像目标检测和识别方法 ,该方法根据SAR图像统计分布特性 ,结合恒虚警检测算法和小波变换提取感兴趣的SAR图像目标特征 ,检测得到目标 ,采用马氏距离从杂波背景中识别该目标。实际SAR图像测试结果表明了该方法的有效性     

群体决策中不精确结论综合模型的研究

采用关系化简、等价类划分和排序选择等步骤对群体决策中的不精确结论进行综合,可以有效地处理群体决策中的不精确结论综合问题,提高群体决策系统的性能.     

一种高分辨率谱估计与数据外推的快速算法

利用信号频谱幅度分布的先验信息,对短时数据序列信号提出了一种实现高分辨率谱估计和数据序列外推的快速算法。该算法利用了算子矩阵的特殊结构,采用简单、快速的矩阵求逆算法,使算法的运算量和数据存储容量大幅度下降。给出了算法在高分辨率谱估计及数据序列外推中的应用实例和仿真结果,证实了该算法的优良性能。     

Spectral Properties and Positivity of Flows in Infinite Networks with Dynamic Boundary Control Nodes

In this paper we study transport processes on infinite networks with dynamic boundary control nodes. These flows can be modeled by operator semigroups on a suitable Banach space. Using functional analytical and graph theoretical methods, we investigate its spectral properties of the system and positivity of the semigroup under appropriate assumptions on the network.     

Robust H∞ filtering for discrete-time systems with Markovian switching and time-delays

The robust H∞ filtering problem for uncertain discrete-time Markovian jump linear systems with modedependent time-delays is investigated. Attention is focused on designing a Markovian jump linear filter that ensures robust stochastic stability while achieving a prescribed H∞ performance level of the resulting filtering error system, for all admissible uncertainties. The key features of the approach include the introduction of a new type of stochastic Lyapunov functional and some free weighting matrix variables. Sufficient conditions for the solvability of this problem are obtained in terms of a set of linear matrix inequalities. Numerical examples are provided to demonstrate the reduced conservatism of the proposed approach.     

Capacity analysis of high-rank line-of-sight MIMO channels

Matrix perturbation theory is utilized to investigate high-rank line of sight multiple input multiple output channels in a microwave relay system. The upper and lower bounds of channel capacity are derived based on space time block codes technique and singular values decomposition. A useful constraint for designing LOS MIMO channels is developed by the use of the condition number of the MIMO channel matrix. The theoretical analysis of channel capacity is confirmed by the simulation. The results show that the proposed method is able to give a physical explanation of the high-rank LOS MIMO channel matrix characteristics.