具有全局收敛性的盲均衡算法

为了解决传统的自适应均衡技术需发送训练序列的问题,采用盲均衡技术,利用接收信号本身的特征使均衡器收敛。提出了一种新的盲均衡算法(C&D算法),该算法将CRIMNO算法和判决引导(Decision Directed,DD)算法相结合,利用信号序列间的互不相关特性,从而使其具有全局收敛性能。实验结果表明:与CRIMNO算法相比,在相同的信噪比下,该算法具有收敛快速、运算量少和残留误差小的特点。     

履带车辆动力舱空气流场的CFD模拟与试验研究

以某履带车辆动力舱为研究对象，建立了舱内空气流动与传热计算的物理模型和数学模型，采用标准k-ε方程湍流模型对动力舱内的空气流动进行了描述，采用Fluent软件中的薄面模型对散热器与冷却风扇进行了简化处理，对舱内空气的速度场和温度场进行了三维数值模拟，采用热线风速仪对进、排气窗处的气体流速与温度进行了试验测试，测试值与模拟值的最大相对误差为9．42％，精度能够满足工程需要，表明该计算模型合理可行。     

On gamma estimation via matrix kriging

In financial engineering, sensitivities of derivative prices (also known as the Greeks) are important quantities in risk management, and stochastic gradient estimation methods are used to estimate them given the market parameters. In practice, the surface (function) of the Greeks with respect to the underlying parameters is much more desired, because it can be used in real‐time risk management. In this paper, we consider derivatives with multiple underlying assets, and propose three stochastic kriging‐based methods, the element‐by‐element, the importance mapping, and the Cholesky decomposition, to fit the surface of the gamma matrix that can fulfill the time constraint and the precision requirement in real‐time risk management. Numerical experiments are provided to illustrate the effectiveness of the proposed methods.