An Improved Composite Multiscale Fuzzy Entropy for Feature Extraction of MI-EEG

Motor Imagery Electroencephalography (MI-EEG) has shown good prospects in neurorehabilitation, and the entropy-based nonlinear dynamic methods have been successfully applied to feature extraction of MI-EEG. Especially based on Multiscale Fuzzy Entropy (MFE), the fuzzy entropies of the τ coarse-grained sequences in τ scale are calculated and averaged to develop the Composite MFE (CMFE) with more feature information. However, the coarse-grained process fails to match the nonstationary characteristic of MI-EEG by a mean filtering algorithm. In this paper, CMFE is improved by assigning the different weight factors to the different sample points in the coarse-grained process, i.e., using the weighted mean filters instead of the original mean filters, which is conductive to signal filtering and feature extraction, and the resulting personalized Weighted CMFE (WCMFE) is more suitable to represent the nonstationary MI-EEG for different subjects. All the WCMFEs of multi-channel MI-EEG are fused in serial to construct the feature vector, which is evaluated by a back-propagation neural network. Based on a public dataset, extensive experiments are conducted, yielding a relatively higher classification accuracy by WCMFE, and the statistical significance is examined by two-sample t-test. The results suggest that WCMFE is superior to the other entropy-based and traditional feature extraction methods.     

信息安全风险评估的模糊多准则决策方法

基于ISO/IEC17799标准建立了一个综合的信息系统风险分析框架,并运用模糊多准则决策(FMCDM)方法计算信息安全风险,根据风险等级矩阵(RLM)对信息资产风险进行级别划分,最终建立评估信息资产相关风险的完整模型。     

An Improved Immune Genetic Algorithm for Solving the Optimization Problems of Computer Communication Networks

1　IntroductionIndesigningacomputercommunicationnet work ,thenetworkaveragedelayisanimportantpa rameterinthenetworkperformance .Inthispaper,weonlyconsiderM /M/1networks,whichmeansthatthemessageprocessingtimeisaprobabilisticdensityfunctionwithnegativepower,thegroupar rivalandsendingisofPoissiondistributionwithasinglequeue .Supposethatthenetworktopologicalstructureandtheestimatesoftheexternaltrafficrequirementsaregiven ,howtoselecttheoptimalroutestobeusedbythecommunicatingnodesinthenetworksoast…     

一个基于相邻像素兼容度的模糊加权平均滤波器

在文献[1]的基础上，提出几个改进的模糊加权平均滤波器。本文的方案不仅同时考虑了相邻像素对中心像素的兼容性以及中心像素对相邻像素的兼容性，而且还考虑到了权系数对局部环境的适应性。实验结果表明，该方法相比文献[1]中的模糊加权平均滤波器以及标准的均值滤波器、中值滤波器在噪声消除与边缘保留方面具有更好的性能。     

多传感器目标的模糊识别

根据模糊理论，采用信息融合技术和模糊识别技术，讨论了在多类传感器网内进行多目标模糊识别的一般原理和方法。     

一类连续模糊动态系统控制方法在Furuta摆中的应用

为了研究Furuta摆在倒立点附近的稳定控制问题，采用基于T-S模糊模型的一类连续模糊动态系统控制方法，首次进行Furuta摆的模糊状态空间建模，并采用模糊切换的思想，设计了Furuta摆在倒立点附近的稳定控制器，进而分析了系统稳定性。与已有的方法相比，该方法的优点是稳定区域大、调节时间短。数字仿真结果验证了方法的有效性。     

双波长稳频CO_2激光模糊控制系统的建模与优化

报导一种模糊逻辑控制系统的建模与优化方法。以此方法设计的模糊逻辑控制器，用于双波长稳频ＣＯ２激光器的控制得到令人满意的结果。     

可重构制造系统重组过程中设备选择模型的研究

根据生产任务选择加工设备进行制造资源重组是实现可重构制造系统的关键问题之一，由于设备的选择涉及到多种因素，既有定量指标，又有定性指标，传统的依靠人工经验的方法显得力不从心。本文首先结合实际情况，提出了一套设备选择评价体系，通过对模糊判断矩阵采用最小对数二乘法确定各评价因素的权重系数，针对定性指标和定量指标采用不同的方法确定其性能指标值，通过模糊积分对评判指标进行综合评判，最后进行了实例研究。所提出的方法有效地简化了决策过程，为可重构制造系统设备选择提供了一套行之有效的方法。     

Stochastic techniques for global optimization: A survey of recent advances

In this paper stochastic algorithms for global optimization are reviewed. After a brief introduction on random-search techniques, a more detailed analysis is carried out on the application of simulated annealing to continuous global optimization. The aim of such an analysis is mainly that of presenting recent papers on the subject, which have received only scarce attention in the most recent published surveys. Finally a very brief presentation of clustering techniques is given.     

具有模糊数的模糊多目标群体决策优选模型与方法

多目标群体决策问题是运筹学的一个重要研究领域，目前已经提出了一些有效的决策方法。但对目标值和权重均为模糊数的模糊多目标群体决策问题却研究不多，本对此类模糊多目标群体决策问题进行了探讨，利用相对正理想方案与相对负理想方案概念定义了相对差异距离，进而建立了模糊多目标群体决策优选模型与方法，并通过战役决心方案的评价说明了该方法是可行、有效的，可作为军事决策与决策支持系统的备选方法。