一种基于新的条件信息量的属性约简算法

为了获得决策系统中更好的相对约简,讨论了属性约简与条件信息量的关系,提出了新的条件信息量,由此定义新的属性重要性。统一了一致决策表和不一致决策表属性约简方法,以新的属性重要性为启发信息,给出了计算新的条件信息量的高效算法。理论分析和实验结果表明,与现有的基于条件信息量的约简算法相比,该算法时间复杂度较低,同时约简后的属性数目更少。     

Stability analysis of the simplest Takagi-Sugeno fuzzy control system using circle criterion

A frequency-domain-based sufficient condition is derived to guarantee the globally asymptotic stability of the simplest Takagi-Sugeno (T-S) fuzzy control system by using the circle criterion. The analysis is performed in the frequency domain, and hence the condition is of great significance when the frequency-response method, which is widely used in the linear control theory and practice, is employed to synthesize the simplest T-S fuzzy controller. Besides, this sufficient condition is featured by a graphical interpretation, which makes the condition straightforward to be used. Comparisons are drawn between the performance of the simplest T-S fuzzy controller and that of the linear compensator. Two numerical examples are presented to demonstrate how this sufficient condition can be applied to both stable and unstable plants.     

黑龙江省低山丘陵区水保措施减蚀效应研究

黑龙江省低山丘陵区土壤贫瘠,农业生产活动剧烈,加之降雨多以夏季暴雨为主,造成了严重的土壤侵蚀现象。通过对宾县三岔河小流域7个试验小区径流和产沙观测资料的分析,总结得出不同水保措施下的水土保持效益,为合理安排耕作方式提供参考。图1,表2,参16。     

线性定常模糊随机系统的响应分析

证明了线性定常模糊随机系统的输出在均方意义下的收敛性,并给出了系统响应的模糊概率特征关系方程。     

基于小波分析的噪声抑制和数据压缩综合技术——SAR图像的噪声抑制与数据压缩

本文给出了一种基于小波分析方法的噪声抑制技术,它具有运算简便和能在保持原图精度的同时有效地降低斑点噪声影响的优点。更重要的是,它将噪声抑制与数据压缩过程同时进行,对ＳＡＲ雷达图像的处理取得了良好的效果。     

Multi-label dimensionality reduction and classification with extreme learning machines

In the need of some real applications, such as text categorization and image classification, the multi-label learning gradually becomes a hot research point in recent years. Much attention has been paid to the research of multi-label classification algorithms. Considering the fact that the high dimensionality of the multi-label datasets may cause the curse of dimensionality and wil hamper the classification process, a dimensionality reduction algorithm, named multi-label kernel discriminant analysis （MLKDA）, is proposed to reduce the dimensionality of multi-label datasets. MLKDA, with the kernel trick, processes the multi-label integrally and realizes the nonlinear dimensionality reduction with the idea similar with linear discriminant analysis （LDA）. In the classification process of multi-label data, the extreme learning machine （ELM） is an efficient algorithm in the premise of good accuracy. MLKDA, combined with ELM, shows a good performance in multi-label learning experiments with several datasets. The experiments on both static data and data stream show that MLKDA outperforms multi-label dimensionality reduction via dependence maximization （MDDM） and multi-label linear discriminant analysis （MLDA） in cases of balanced datasets and stronger correlation between tags, and ELM is also a good choice for multi-label classification.     

属性约简的两阶段遗传算法

属性约简是数据挖掘的一个重要研究内容. 为了解决具有多种属性类型的决策表约简问题,在粗集和二元关系聚合理论的基础上,利用属性重要性作为评价标准,提出了一种两阶段遗传约简算法. 算法的第一阶段是为了找出尽可能多的约简,第二阶段力求寻找最小约简. 根据算法每个阶段的目标设计了编码方案、种群规模、适应度函数、终止条件、选择、变异和修正操作. 实验表明,与标准遗传算法相比,两阶段算法在计算最小约简时更为准确和稳定.     

高校计算机安全事件应急响应组织的构建

在阐述应急响应的概念、应急响应组织产生的必要性及发展情况的基础上，分析了校园网络环境的特点和安全风险，以及计算机应急响应系统的职能，并据此提出高校校园网应急响应组织的总体架构。     

光纤耦合器对光谱响应的研究

 通过对耦合的理论分析,模拟了实际的拉锥过程,构建了光纤耦合器对光谱响应特性的理论模型。详细分析了不同熔烧长度和不同拉伸距离对光谱响应的影响,熔烧长度越短,拉锥曲线震荡越剧烈,到达归一化光功率为0.5所需要的拉伸长度越短,会出现更多的震荡包络;拉伸距离越长,产生的包络震荡越多,波长间隔越密,对光谱响应越为敏感,从实验中验证其合理性。这一模型的建立将大大减少实际工作中的盲目性,对光纤耦合器制作有一定的指导意义。     

基于双稳阱内随机共振的OFDM信号检测方法研究

为了解决OFDM(orthogonal frequency division multiplexing)传输系统中接收端对微弱OFDM信号的检测问题,本文将双稳阱内随机共振系统与OFDM信号增强和解调过程相结合,推导了多载波信号激励下双稳阱内随机共振系统从零状态变化到势阱状态所需时间的解析表达式,分析了暂态响应导致的多载波信号在一个符号内的能量损失问题;推导了系统稳态输出方程,分析了稳态过程对子载波已调信号叠加直流偏置分量的问题;探讨了在不同系统参数和噪声强度下阱内随机共振对OFDM信号解调性能的影响。仿真结果表明：该方法可有效实现信号与噪声阱内协同作用,提高OFDM信号的检测性能。