尝试教学法与数学创新能力的培养

文章针对初中传统数学教学中存在的教学目的、方向不明确、教学方法不妥当等问题,探讨了尝试教学法在数学课堂教学的创新、教师创新精神与学生创新能力培养等方面的作用。     

整旧如旧与整旧如新——《古代文论》课程教学之我见

《古代文论》的教学在汉语言文学本科专业课程教学中因为跨度大,内容繁杂,同时又是理论课而显得老师讲解、学生理解比较困难。文字梳理在该门课程的讲解与学习中是一个最大的难点。在这个方面,应该注意“整旧如旧”和“整旧如新”原则的双向配合。     

熵理论在装备保障指挥组织结构优化中的应用

把熵理论应用于装备保障指挥组织结构的优化设计,并以某军区装备部机关组织结构为例,从量化的角度比较改革前后组织结构的时效熵和质量熵,得出结论:改革后的军区装备部机关组织结构有序度优于改革前机关组织结构有序度。     

有界波模拟器远场辐射特性仿真研究

利用电磁仿真计算软件FEKO对有界波模拟器远场辐射特性进行仿真分析,得到远场的辐射方向图,并指出方向图随激励源频率的变化关系。该结论对开展电磁防护研究及快上升沿电磁脉冲场模拟器的设计具有一定的参考意义。     

基于小波变换和数据融合的多导联ECG信号QRS波群精确检测算法

本文首先对单导联心电图（ Ｅ Ｃ Ｇ）信号的小波变换进行假设检验，得到 Ｑ Ｒ Ｓ波群的位置和检验的虚警漏报概率，然后对 １２ 导联检测结果作峰点比对融合和决策加权融合处理，最终得到精确的 Ｑ Ｒ Ｓ位置。实验表明这种方法对各种主要病症的 Ｑ Ｒ Ｓ波群均能准确检出，正确率在 ９９９５％ 以上。     

导弹系统安全性分析中的引发事件鉴别方法

引发事件鉴别是基于事故机理安全性分析的首要任务。鉴别结果是否全面、完整直接影响最终分析结果的有效性。导弹系统安全风险涉及面广、影响因素多,需要系统的可操作方法来指导引发事件的鉴别工作。针对导弹工作特点,提出考虑导弹任务剖面,运用主逻辑图对导弹进行系统性的层次化描述,对引发事件进行整理和归纳。将危险与可操作性分析引入导弹系统安全性分析中进行引发事件鉴别,结合故障模式影响分析,支持对单一故障类和参数异常类引发事件的鉴别。结果表明,所提框架为解决导弹系统安全性分析中引发事件鉴别的系统性完整性提供了可行的思路。     

基于LMD频域近似熵频谱感知算法研究

针对现有频域近似熵频谱感知技术在低信噪比条件下抗噪声性能和检测性能有待提升的问题,提出了一种基于LMD频域近似熵的频谱感知算法。(1)算法筛选出3个PF分量累加求和,使得算法提取局部调频包络特征信息得到最优,进一步排除噪声不确定度的影响。(2)算法对累加PF分量进行频域变换后求其近似熵,增强算法对频域信息的嗅探能力,提升算法检测性能。Monte Carlo仿真结果表明,在噪声不确定度为0dB,采样点数为8 000的情况下,当信噪比大于-19 d B时,可以对2ASK信号达到100%的检测概率,与现有频域近似熵算法相比,检测性能约有17 d B的提升。     

海天背景下舰船可见光图像目标区域定位方法

针对行均值法用于海天背景下舰船目标区域定位可靠性不高、容易受到舰船目标大小和海天背景复杂程度影响的不足,提出一种基于图像行灰度熵的舰船目标区域定位方法。该方法在分析海天背景下舰船目标可见光图像成像特点基础上,结合信息熵理论给出了图像灰度熵及行灰度熵的概念,利用图像行灰度熵描述图像在行方向上的灰度变化程度,选用滑动区间方差搜索策略得到图像行灰度熵曲线的突变区间,从而实现舰船目标区域定位,最后通过实际图像进行了实验验证。实验结果表明,该方法能对舰船目标所在区域有效定位,其准确性及鲁棒性均优于行均值法。     

Information theory for ranking and selection

We study the classical ranking and selection problem, where the ultimate goal is to find the unknown best alternative in terms of the probability of correct selection or expected opportunity cost. However, this paper adopts an alternative sampling approach to achieve this goal, where sampling decisions are made with the objective of maximizing information about the unknown best alternative, or equivalently, minimizing its Shannon entropy. This adaptive learning is formulated via a Bayesian stochastic dynamic programming problem, by which several properties of the learning problem are presented, including the monotonicity of the optimal value function in an information-seeking setting. Since the state space of the stochastic dynamic program is unbounded in the Gaussian setting, a one-step look-ahead approach is used to develop a policy. The proposed policy seeks to maximize the one-step information gain about the unknown best alternative, and therefore, it is called information gradient (IG). It is also proved that the IG policy is consistent, that is, as the sampling budget grows to infinity, the IG policy finds the true best alternative almost surely. Later, a computationally efficient estimate of the proposed policy, called approximated information gradient (AIG), is introduced and in the numerical experiments its performance is tested against recent benchmarks alongside several sensitivity analyses. Results show that AIG performs competitively against other algorithms from the literature.     

Economic impact of the ministry of defence’s budget: methodological design and results for the Spanish economy

This article analyses the economic impact of the expenditure budget of the Spanish Ministry of Defence (MoD) and its Autonomous Agencies (AA), distinguishing direct, indirect and induced effects. The input–output methodology is used to find intersectoral effects on the rest of the economy. The article quantifies the economic impact in terms of production, gross value added (GVA), employed population, tax revenue, and also in terms of its contribution to the gross domestic product (GDP) of Spain in 2010. The results show that the activity of the MoD and AA generates 1.2% of the country’s GDP and 1.7% of total employment in that year.