采用区分性幅相联合字典学习的低截获概率信号分离方法

为解决采用字典学习的信号分离方法存在的相位信息缺失和子字典交叉表示问题，提出一种区分性幅相联合字典学习方法。该方法针对相位信息缺失问题，构建了幅相联合字典模型；针对混合信号在联合字典上投影时存在的交叉表示问题，基于区分性字典学习思想提出在字典学习过程目标函数中加入交叉表示抑制项。仿真结果表明：幅相联合字典能够充分表示典型低截获概率信号的幅相信息，交叉表示抑制项能有效抑制信号间的交叉表示，算法具有良好的分离性能。     

内隐学习的特征及对其本土教育的启示

内隐学习就是无意识获得刺激环境中复杂知识的过程。在无意识研究热潮中，内隐学习研究获得了很大的发展。内隐学习的研究对于理解人类认识过程的本质，特别是对于探明人们获得丰富复杂知识的心理机制提供了全新的视野。本文着重探讨内隐学习的特征以及对本土教育的启示。     

英语教学中自主学习能力的培养

自主学习是语言学习的关键，学生是否能够学好外语取决于自主学习能力的培养。本文阐述了自主学习的理论基础及使用价值，如何培养学生自主学习的能力，更多关注学习方法的相互作用。     

初中生学习动机与自我监控学习行为关系研究

采用问卷调查法对新疆石河子市初中生的学习动机及自我监控学习行为进行测查，并分析其相关性，结果表明：不同性别、年级初中生的四种学习动机强度有差异，自我监控学习行为水平也有显著差异；成就性动机、威信性动机、认知性动机与自我监控学习行为均有显著正相关，附属性动机与其无明显相关。     

公安现役院校英语学习环境的调查与思考

学习环境对于语言学习者至关重要,就外部环境和内部环境相互关系而言,外部环境影响人的学习态度和认知过程,内部环境控制外部环境的影响力。这些因素无疑能促进英语学习,但也可能在某种程度上阻碍英语学习的进步。在对几所公安现役部队院校的英语学习环境调查后发现,英语学习环境不容乐观,还有很多急需改进之处,应引起有关方面的重视。     

Optimal production ramp-up in the smartphone manufacturing industry

Motivated by challenges in the smartphone manufacturing industry, we develop a dynamic production ramp-up model that can be applied to economically satisfy nonstationary demand for short-life-cycle products by high-tech companies. Due to shorter life cycles and more rapid evolution of smartphones, production ramp-up has been increasingly critical to the success of a new smartphone. In the production ramp-up, the key challenge is to match the increasing capacity to nonstationary demand. The high-tech smartphone manufacturers are urged to jointly consider the effect of increasing capacity and decreasing demand. We study the production planning problem using a high-dimensional Markov decision process (MDP) model to characterize the production ramp-up. To address the curse of dimensionality, we refine Monte Carlo tree search (MCTS) algorithm and theoretically analyze its convergence and computational complexity. In a real case study, we find that the MDP model achieves revenue improvement by stopping producing the existing product earlier than the benchmark policy. In synthetic instances, we validate that the proposed MCTS algorithm saves computation time without loss of solution quality compared with traditional value iteration algorithm. As part of the Lenovo production solution, our MDP model enables high-tech smartphone manufacturers to better plan the production ramp-up.     

大学英语听说能力培养及策略

大学英语听说课是提高学生英语综合技能的训练课。听说教学，要坚持以学生为主体的教学观，从分析和解决问题入手，运用任务型教学和合作学习等模式，实施多种教学策略，帮助学生打好语言基本功，提高文化素养，全面培养学生的英语交际能力。     

A misclassification cost‐minimizing evolutionary–neural classification approach

Machine learning algorithms that incorporate misclassification costs have recently received considerable attention. In this paper, we use the principles of evolution to develop and test an evolutionary/genetic algorithm (GA)‐based neural approach that incorporates asymmetric Type I and Type II error costs. Using simulated, real‐world medical and financial data sets, we compare the results of the proposed approach with other statistical, mathematical, and machine learning approaches, which include statistical linear discriminant analysis, back‐propagation artificial neural network, integrated cost preference‐based linear mathematical programming‐based minimize squared deviations, linear integrated cost preference‐based GA, decision trees (C 5.0, and CART), and inexpensive classification with expensive tests algorithm. Our results indicate that the proposed approach incorporating asymmetric error costs results in equal or lower holdout sample misclassification cost when compared with the other statistical, mathematical, and machine learning misclassification cost‐minimizing approaches. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006.     

基于学习矢量量化(LVQ)神经网络的雷达体制识别

由于现代战争中雷达体制的多样化、复杂化及其综合应用使得雷达体制识别中要处理大量复杂的高维数据,学习矢量量化(LVQ)神经网络不仅能处理有监督分类,而且相对于其他神经网络能以较小的计算量处理大量输入数据,所以采用LVQ对雷达体制进行识别,同时针对LVQ学习速率的变化可能引起学习算法不稳定,采用修正的学习速率算法.在简要介绍雷达体制和LVQ的基础上构造了LVQ神经网络对雷达体制进行分类.通过与径向基神经网络(RBFN)识别算法的仿真对比,证实了方法的有效性.     

二语习得理论在大学英语教学中的应用

如何能把英语学好,这是英语学习者最为关心的问题。而英语教育工作者关注的问题则是,如何能把教学搞好,教学工作的核心是什么。根据二语习得理论,关键是采取多种教学方式,对学生进行有效的语言输入,给学习者建立一个理想的英语习得环境。