Pragmatic Approach to Adaptive Turbo Coded Modulation

This paper presents a pragmatic adaptive scheme for TuCM over slowly fading channels. The adaptive scheme employs a single turbo coded modulator composed of a variable-rate turbo encoder and a variable-rate variable-power MQAM for all fading regions, so it has an acceptable complexity to implement. The optimal adaptive TuCM scheme is determined subject to various system constraints. Simulations have been performed to measure the performance of the scheme for different parameters. It is shown that adopting both the turbo coded modulator and the transmit power achieves a performance within 2.5 dB of the fading channel capacity.     

网络外部性、转移成本与企业兼容性选择

从转移成本内生化的角度,研究了存在网络外部效应的市场中,进入企业的兼容性选择问题,并将其与在位企业、行业以及政府管制下的兼容性动机进行比较.本文得出的主要结论是相对社会最优而言,由于转移成本的不同,进入厂商可能兼容性选择不足,也可能过度兼容.     

基于MATLAB的神经网络在股市预测中的应用

以道氏三大假说作为理论基础，设计一个三层BP网络，并建立相应的数学模型，以MATLAB为工具，个股上海石化(600688)140天实际收盘价作为样本，对网络进行训练后，预剩10天的收盘价，并计算出与实际收盘价的高差Q＝0．0146，Q已经小到几乎可以忽视的程度。     

侧风状况下轿车气动特性的仿真与实验研究

以获得适合计算侧风气动特性的湍流模型为目的,应用计算流体动力学方法对比了标准k模型、RNG k模型、Realizable k模型以及SST模型对不同横摆角状态下轿车气动特性仿真结果的影响。结果表明,当0时,采用Realizable k湍流模型仿真得出的阻力系数与实验结果最为吻合,误差仅为1.53%,侧力系数的仿真结果与理论分析更为吻合;当3～1 5时,采用Realizable k湍流模型仿真得出的阻力系数与实验结果相比误差最大为0.96%,侧力系数的仿真结果与实验结果趋势一致,误差最大也仅为4.9%。总之,Realizable k湍流模型能够很好的模拟侧风状态下车辆的气动特性,仿真结果为进一步分析车辆的侧风稳定性提供了参考数据。     

虚拟环境中一种基于密度聚类的区域划分算法

为支持虚拟环境中大规模用户共享资源,需解决虚拟空间中用户集合划分问题,即把用户对象分配给多个服务器。由于用户不可预知的移动和交互,可能导致部分服务器负载过重。现有的划分思想注重于服务器负载的重分配,但是用户的移动和交互为划分也应作为主要考虑因素。据此思路,提出一种基于密度聚类的改进型划分算法(DCA)。该方法改进密度聚类中的邻域半径(Eps)和最小数目阈值(MinPts)因子,提出了基于移动视窗方法的密度聚类方法。同时,提出不一致性事件的概念以验证所提方法的有效性,并给出了实验结果。     

Multi-attribute decision making method for air target threat evaluation based on intuitionistic fuzzy sets

The function of the air target threat evaluation (TE) is the foundation for weapons allocation and senor resources management within the surface air defense. The multi-attribute evaluation methodology is utilized to address the issue of the TE in which the tactic features of the detected target are treated as evaluation attributes. Meanwhile, the intuitionistic fuzzy set (IFS) is employed to deal with information uncertainty in the TE process. Furthermore, on the basis of the entropy weight and inclusion-comparison probability, a hybrid TE method is developed. In order to accommodate the demands of naturalistic decision making, the proposed method allows air defense commanders to express their intuitive opinions besides incorporating into the threat features of the detected target. An illustrative example is provided to indicate the feasibility and advantage of the proposed method.     

Simulation method for reliability of TT&C mission with high redundancy and small time horizon

The tracking, telemetry and command (TT&C) mission is extremely reliable for its characters of small time horizon and high redundancy. The combined forcing and failure biasing (CFFB) method that is usually used for simulating the unreliability of the highly dependable mission system seems not so efficient for the TT&C mission. The concept about the importance of failure transition is proposed based on the logical relationship between TT&C mission and its involved resources. Then, the importance is used for readjusting the transition rate of the failure transition when using the forcing and failure biasing during the simulation. Examples show that the improved CFFB method can evidently increase the occurrence of the TT&C mission failure event and decrease the sample variance. More redundancy of the TT&C mission leads to the improved CFFB method more efficient.     

动态需求的多车型车辆调度问题及云遗传算法

根据动态信息产生的时间点不同提出时间轴概念,利用时间轴将动态车辆调度问题转化为一系列的静态车辆调度问题,建立考虑车载率和油耗的综合费用为优化目标的车辆调度模型.利用云模型云滴的随机性和稳定倾向性改进自适应遗传算法中交叉率和变异率设置方式,设计云自适应遗传算法对车辆调度问题进行实时再优化.最后,结合算例对模型和算法的有效性进行验证.     

基于Bagging-SVM动态集成的多极化HRRP识别

针对多极化高分辨率一维距离像（high range resolution profile, HRRP）在目标识别过程中存在计算量和数据量大、识别算法复杂的问题,提出一种基于Bagging-SVM动态集成的目标识别方法。该方法首先提取多极化HRRP平移不变特征向量,然后运用Bagging方法结合基于动态互信息的特征选择方法生成基分类器,最后引入基分类器差异度进行选择性集成。实验验证该方法在缩减数据规模和计算量的同时,能有效利用多极化特征信息,得到较高的分类正确率,并且松弛了HRRP目标的姿态敏感性。     

An interval method for studying the relationship between the Australian dollar exchange rate and the gold price

This paper proposes an interval method to explore the relationship between the exchange rate of Australian dollar against US dollar and the gold price,using weekly,monthly and quarterly data.With the interval method,interval sample data are formed to present the volatility of variables. The ILS approach is extended to multi-model estimation and the computational schemes are provided. The empirical evidence suggests that the ILS estimates well characterize how the exchange rate relates to the gold price,both in the long-run and short-run.The comparison between the interval and point methods indicates that the difference between the OLS and the ILS estimates is increasing from weekly data to quarterly data,since the lowest frequency point data lost the most information of volatility.