基于连分式的广义高斯分布的参数估计

近年来,使用广义高斯分布拟合的子带小波系数的统计模型被广泛地用于图像分类、修复、去噪和分析等图像处理中,而广义高斯分布的参数拟合问题一直是该领域中的一个重要的瓶颈问题。文章针对该问题提出用连分式迭代来实现广义高斯分布的参数估计,连分式迭代具有算法稳定、收敛域广、计算精度高、迭代速度快等特性;构造了基于连分式的广义高斯分布形状参数β的迭代格式。实验结果表明在不同方差噪声时,基于连分式迭代算法在计算时间复杂度和精度上优于牛顿迭代算法,而且收敛性不受初始值等参数制约,总能收敛到最优值附近。     

Process capability analysis and estimation scheme for autocorrelated data

<正>Autocorrelation is prevalent in continuous production processes,such as the processes in the chemical and pharmaceutical industries.With the development of measurement technology and data acquisition technology,sampling frequency is getting higher and the existence of autocorrelation cannot be ignored.This paper analyzes five estimation schemes of process capability for autocorrelated data.Comparisons among these schemes are discussed for small sample and large sample.In conclusion,this paper gives a procedure of process capability analysis for autocorrelated data.     

Robust Sensor Bias Estimation for Ill-Conditioned Scenarios

Sensor bias estimation is an inherent problem in multi-sensor data fusion systems. Classical methods such as the Generalized Least Squares (GLS) method can have numerical problems with ill-conditioned sets which are common in practical applications. This paper describes an azimuth-GLS method that provides a solution to the ill-conditioning problem while maintaining reasonable accuracy compared with the classical GLS method. The mean square error is given for both methods as a criterion to determine when to use this azimuth-GLS method. Furthermore, the separation boundary between the azimuth-GLS favorable region and that of the GLS method is explicitly plotted. Extensive simulations show that the azimuth-GLS approach is preferable in most scenarios.     

Experimental Analysis of Link Estimation Methods in Low Power Wireless Networks

Wireless sensor networks are envisioned to be an integral part of cyber-physical systems,yet wireless networks are inherently dynamic and come with various uncertainties.One such uncertainty is wireless communication itself which assumes complex spatial and temporal dynamics.For dependable and predictable performance,therefore,link estimation has become a basic element of wireless network routing.Several approaches using broadcast beacons and/or unicast MAC feedback have been proposed in the past years,but ...     

RBF神经网络在商品住宅投资估算中的应用

投资估算是建筑工程项目可行性研究中关键性的工作,其结果直接影响投资决策的判断。针对现行人工神经网络估算方法,输入向量的选择依据科学性不足的缺陷,笔者拟应用解释结构模型(Interpretatiue Sructral Modelling,ISM),分析影响商品住宅造价的因素,对造价影响程度不同的影响因素划分层级,以选出对造价影响较大的因素作为输入向量,使人工神经网络在投资估算中的应用更有可靠性。     

Consecutive tracking for ballistic missile based on bearings-only during boost phase

This paper proposes a modified centralized shifted Rayleigh filter(MCSRF) algorithm for tracking boost phase of ballistic missile(BM) trajectory with a highly nonlinear dynamical model based on bearings-only.This paper contributes three folds.Firstly,the mathematical model of an MCSRF for multiple passive sensors is derived.Then,minimum entropy based onedimensional optimization search to adaptively adjust the probability of the different filters for real time state estimation is deployed.Finally,the unscented transform(UT) is introduced to resolve the asymmetric state estimation problem.Simulation results show that the proposed algorithm can consecutively track the BM precisely during the boost phase.In comparison with the unscented Kalman filter(UKF) algorithm,the proposed algorithm effectively reduces the tracking position and velocity root mean square(RMS) errors,which will make more sense for early precision interception.     

化工物性数据库CPPDB在IBM-PC/XT机上的实现

讨论了文题实现方法,介绍了该数据库的总体结构。CPPDB利用dBASE Ⅲ支持建库,数据独立性高,修改、扩充方便。CPPDB存储了468种物质的29种物性数据,具有较强的物性估算和图形输出功能。     

正态分布随机参数的一种估计方法

本文提出了一种最大似然估计方法,可对一般非线性模型中服从正态分布的随机参数的均值、协方差矩阵及其在各观测时刻的取值进行合理的估计。     

统计参数估值方法在检测中应用

本文论述由观测值对检测参数进行统计估值的方法。先建立包含统计误差的观测值数学模型,再进行参数估值。其优点是一方面可以对参数检测方法的精密度和系统误差进行统计分析;另一方面可以把检测问题转化为统计参数估值问题,并应用当今大量的统计估值理论和方法以及计算机软件。     

一类产品失效时间的预测方法

在可靠的工程中,运用灰色控制系统的理论,本文提出了一种寿命分布服从威布尔分布的产品失效时间的预测方法。