When are observed failures more informative than observed survivals?

A framework involving independent competing risks permits observing failures due to a specific cause and failures due to a competing cause, which constitute survival times from the cause of primary interest. Is observing more failures more informative than observing survivals? Intuitively, due to the definitiveness of failures, the answer seems to be the former. However, it has been shown before that this intuition holds when estimating the mean but not the failure rate of the exponential model with a gamma prior distribution for the failure rate. In this article, we address this question at a more general level. We show that for a certain class of distributions failures can be more informative than survivals for prediction of life length and vice versa for some others. We also show that for a large class of lifetime models, failure is less informative than survival for estimating the proportional hazards parameter with gamma, Jeffreys, and uniform priors. We further show that, for this class of lifetime models, on average, failure is more informative than survival for parameter estimation and for prediction. These results imply that the inferential purpose and properties of the lifetime distribution are germane for conducting life tests. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

多序列跳频无线通信系统抗多音干扰性能研究

常规跳频系统（FH-2FSK）发送的调制信号易被干扰损伤,提出的多序列跳频（MSFH）无线通信方式不需对载波进行调制,直接以载波频率来表示消息,且每跳所使用频点的随机性比FH-2FSK强．通过理论分析得到了加性白高斯噪声信道下存在多音干扰时MSFH系统误码率的闭合表达式,由数值和仿真结果可知,在信道中仅存在加性白高斯噪声时,MSFH与FH-2FSK误码率性能相同;在最坏多音干扰下,MSFH与FH-2FSK相比约有3dB误码率性能增益,抗多音干扰能力更强．     

导频设计的MIMO-OFDM改进信道估计算法

为提高系统的传输效率并改善信道估计的性能,提出了一种结合优化导频设计的分段带阻滤波算法.采用优化的导频设计,该算法在少量增加计算复杂度的基础上,能够进一步提高信道估计的性能,与实际中广泛应用的经典时域滤波算法相比,具有更高的估计精度.仿真结果证明该算法适用于不同的信道环境,尤其在低信噪比的条件下,该算法能够明显降低信道估计的MSE.     

面向时空交通栅格流量预测的3D通道注意力网络

城市交通流量预测对交通管理和公共安全具有重要意义。然而,交通栅格流量数据中的规律在时刻变化,在城市中存在全局范围的时空间关系,并且不同特征通道在每个城市区域上有不同的重要性。为解决这些挑战并做出更准确的预测,设计了一种新颖的时空神经网络模型——3D通道注意力网络(three-dimensional channel-wise attention networks,3D-CANet)。提出一个3D通道内注意力(three-dimensional inner channel attention,3D-InnerCA)单元来动态捕获各个通道中不同的全局时空相关性,同时设计通道间注意力(inter channel attention,InterCA)单元来自适应地重校准每个区域上不同特征通道的贡献。在3个真实交通栅格流量数据集上的实验结果表明,3D-CANet模型的预测能力优于其他对比方法,证明了模型的有效性。     

早期可靠性数据的统计分析及其应用

在大型复杂产品研制过程中,通过原理样机的各类试验所获得的早期可靠性数据对产品早期可靠性的评估及可靠性设计具有重要意义。文中利用顺序约束模型研究了早期可靠性数据的处理方法,并将早期可靠性数据评估结果应用于可靠性增长计划的制定,从而有效减短了可靠性增长试验的时间。最后,给出了一个实际例子,以说明上述方法的应用。     

Bayesian strategies for dynamic pricing in e‐commerce

E‐commerce platforms afford retailers unprecedented visibility into customer purchase behavior and provide an environment in which prices can be updated quickly and cheaply in response to changing market conditions. This study investigates dynamic pricing strategies for maximizing revenue in an Internet retail channel by actively learning customers' demand response to price. A general methodology is proposed for dynamically pricing information goods, as well as other nonperishable products for which inventory levels are not an essential consideration in pricing. A Bayesian model of demand uncertainty involving the Dirichlet distribution or a mixture of such distributions as a prior captures a wide range of beliefs about customer demand. We provide both analytic formulas and efficient approximation methods for updating these prior distributions after sales data have been observed. We then investigate several strategies for sequential pricing based on index functions that consider both the potential revenue and the information value of selecting prices. These strategies require a manageable amount of computation, are robust to many types of prior misspecification, and yield high revenues compared to static pricing and passive learning approaches. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

矩阵变换特征与码序列联合学习的卷积码识别方法

现有基于深度学习的卷积码识别方法仍存在参数规模较大、识别性能较弱等不足。针对该问题,提出了一种基于矩阵变换特征与码序列联合学习的卷积码识别方法。将接收到的码字序列排列成矩阵形式,利用软信息剔除可靠性较低的码字,通过一种新的矩阵变换算法得到特征矩阵。在识别时,将原始码字矩阵和特征矩阵输入到具有多模态数据联合学习能力的网络模型,在神经网络中完成特征的提取融合与卷积码的识别。仿真结果表明,所提方法性能明显优于现有基于深度学习的识别方法,特别是对于高码率卷积码;当码率较低时,同样优于传统识别方法。当信噪比达到5 dB时,25种不同参数卷积码的识别率均可达到100%。     

多进制多维信号集信道容量分析及其计算

描述了信道容量的一般概念 ,具体就波形信道 ,连续信道及离散输入连续输出无记忆信道进行了分析 ,分别导出了它们的信道容量公式。结合几种常见的多进制多维调制技术MPSK、MQAM、L正交信号及其星座分析 ,给出了它们信道容量的Monte Carlo模拟以及数值积分模拟 ,同时分析了由于信号集扩展而带来的编码增益     

俄罗斯舰艇指控系统集成技术分析

首先介绍了俄罗斯正在发展的先进舰艇集成指控系统的体系结构,对舰艇集成指控系统与独立的火控系统之间的功能分配作了论述.分析了对所有类型舰栽武器系统实施集中控制的可能性.并从功能原理的角度较为详细的介绍了舰艇集成指控系统的主要控制通道及其功能.同时还简要分析了该系统的可靠性和战斗生命力保障,并对舰艇指控系统的集成效果作了结论性的分析.最后对俄罗斯舰艇指控系统的发展特点进行了概括总结.希望为我国舰艇指控系统的研究工作提供一些参考.     

无人机时频二维信道估计研究

依据无人机信道快速时变的相关参数，设计了信道估计所需的时频二维插入导频图案，利用最小均方误差准则，采用维纳滤波器，实现了无人机时频二维信道估计。通过性能分析和数值仿真可以看出，基于Wiener滤波MMSE准则设计时频二维信道估计不仅可以提高无人机信道的精度，同时还可以保证信道的鲁棒性能。