Estimation of the Reliability of a Stress–Strength System from Poisson Half Logistic Distribution

This paper discussed the estimation of stress-strength reliability parameter R=P(Y<X) based on complete samples when the stress-strength are two independent Poisson half logistic random variables (PHLD). We have addressed the estimation of R in the general case and when the scale parameter is common. The classical and Bayesian estimation (BE) techniques of R are studied. The maximum likelihood estimator (MLE) and its asymptotic distributions are obtained; an approximate asymptotic confidence interval of R is computed using the asymptotic distribution. The non-parametric percentile bootstrap and student’s bootstrap confidence interval of R are discussed. The Bayes estimators of R are computed using a gamma prior and discussed under various loss functions such as the square error loss function (SEL), absolute error loss function (AEL), linear exponential error loss function (LINEX), generalized entropy error loss function (GEL) and maximum a posteriori (MAP). The Metropolis–Hastings algorithm is used to estimate the posterior distributions of the estimators of R. The highest posterior density (HPD) credible interval is constructed based on the SEL. Monte Carlo simulations are used to numerically analyze the performance of the MLE and Bayes estimators, the results were quite satisfactory based on their mean square error (MSE) and confidence interval. Finally, we used two real data studies to demonstrate the performance of the proposed estimation techniques in practice and to illustrate how PHLD is a good candidate in reliability studies.     

Some Useful Integral Representations for Information-Theoretic Analyses

This work is an extension of our earlier article, where a well-known integral representation of the logarithmic function was explored and was accompanied with demonstrations of its usefulness in obtaining compact, easily-calculable, exact formulas for quantities that involve expectations of the logarithm of a positive random variable. Here, in the same spirit, we derive an exact integral representation (in one or two dimensions) of the moment of a nonnegative random variable, or the sum of such independent random variables, where the moment order is a general positive non-integer real (also known as fractional moments). The proposed formula is applied to a variety of examples with an information-theoretic motivation, and it is shown how it facilitates their numerical evaluations. In particular, when applied to the calculation of a moment of the sum of a large number, n, of nonnegative random variables, it is clear that integration over one or two dimensions, as suggested by our proposed integral representation, is significantly easier than the alternative of integrating over n dimensions, as needed in the direct calculation of the desired moment.     

半线性Klein—Gordon方程Cauchy问题整体解存在定理

本文讨论半线性Klein—Gordon方程Cauchy问题。对初值φ(x)、ψ(x),对空间维数n及半线性项加以适当限制,在Sobolev空间框架下、用不动点原理得到了整体解的存在唯一性。     

东天山的一次暴雨洪水中心最大雨量的估算

本文通过对新疆天山东部地区一次罕见的大暴雨洪水的特征分析，应用水箱模型法和最大熵原理等方法推算出本次大暴雨的中心最大雨量和流域面平均降水量．     

GRCA(1)模型中误差方差自加权估计的渐近分布

考虑随机系数自回归模型Y_t =Φ_ty_t-1+ u_t,其中 Φ_t为随机系数,u_t为随机误差。在允许Φ_t与u_t相依以及Eu_t无穷的条件下,构造了误差方差的自加权估计,并证明了该估计的渐近正态性。最后通过数值模拟,说明 自加权估计的稳健和有效性。     

深海远程正交频分复用水声通信簇约束的分布式 压缩感知信道估计*

在深海远程正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)水声通信中,信道时延较长,导致信道频率选择性衰落严重,传统的压缩感知信道估计算法性能大幅下降。为此,本文利用深海远程信道在一定时间内具有相关性并呈较稳定簇状分布的特点,在分布式压缩感知信道估计中引入簇区域信息,进行簇约束的多数据块联合稀疏信道估计,提出一种簇约束的分布式压缩感知信道估计方法,并在深海开展了定点远程水声通信实验进行验证,实验结果表明,与传统的分布式压缩感知信道估计算法相比,本方法的能够降低50%左右的误码率。     

光纤水听器相位生成载波解调非线性因素的抑制方法

为了消除非线性因素对相位生成载波解调结果的干扰,降低相位生成载波解调过程中低通滤波器的频响特性对相位生成载波解调结果的影响,该文提出了一种基于扩展卡尔曼滤波椭圆参数估计的相位生成载波微分交叉相乘解调方法。该方法在综合考虑各种非线性因素对相位生成载波微分交叉相乘解调结果的影响的基础上,对传统的相位生成载波微分交叉相乘解调过程进行了改进。经过计算机仿真和实验验证,该文所提出的扩展卡尔曼滤波微分交叉相乘方法能够有效地抑制非线性因素对相位生成载波解调结果的干扰,相比传统的相位生成载波微分交叉相乘方法,其信噪比提高了35.0 d B,总谐波失真降低了30.7 dB,信噪谐波比提高了31.0 dB,且扩展卡尔曼滤波微分交叉相乘方法受解调过程中低通滤波器频响特性的影响较小。     

DOA estimation for uniform circular array without the source number based on beamspace transform and higher-order cumulant

Fourth-order cumulant is one of most widely used high-order cumulant for direction of arrival (DOA) estimation due to its ability of expanding the virtual array aperture as well as suppressing Gaussian noise. To address the two-dimensional (2D) DOA estimation problem, we propose a modified MUSIC scheme for uniform circular array (UCA) in this paper. Firstly, the fourth-order cumulant of UCA is considered to construct a new propagator, resulting in the elimination of a priori knowledge of the number of signals. Secondly, the UCA is transformed by beamspace transformation, reducing the time computational complexity of the algorithm since the two-dimensional grid search and singular value decomposition are avoided. And finally a low-rank recovery algorithm is adopted to improve the accuracy regarding the limited snapshots scenario. The numerical simulations validate the superiority of the proposed method.     

大气声传播通道的声源当量估计方法

提出了一种基于大气声传播通道的爆炸声源能量估计方法,通过将计算大气声学的传播能量分布结果与大气中传播的声压幅度衰减模型相结合,使用平流层通道与热层通道传播损失能量比例作为修正量,提高了对爆炸声源能量的估计精度。在多次地面爆炸实验得到的数据中,使用观测距离800 km以上且同时存在平流层通道与热层通道的次声接收信号,对比了平流层顶风速修正的能量估计方法与该文提出的基于大气声传播通道的能量估计方法。实验结果验证了相对于传统风速修正的能量估计方法,该方法可显著降低估计误差。     

稳定分布的多期投资组合模型及其应用

本文研究了多期投资组合模型的问题.利用非正态稳定分布和参数估计的方法,建立了市场上含一个无风险证券和多个风险证券时多期投资组合的模型,对于描述风险证券所具有的偏态和过度峰态的非正态特征及其股市中的应用起到了作用.