Reliability analysis for engineering systems with multiple components has gained increasing interest in recent. Most existing works assume that components follow identical degradation models and preset joint distribut...
详细信息
Reliability analysis for engineering systems with multiple components has gained increasing interest in recent. Most existing works assume that components follow identical degradation models and preset joint distributions or link functions to characterize the degradation interactions. However, distinct degradation characteristics of components are commonly observed in practice. Besides, the degradation interactions are usually complex and diverse, making the preset dependency structures not applicable. Confronted with the diverse degradation characteristics and complex degradation interactions, this paper offers a flexible reliability analysis framework for multi-component systems. First, a stochastic process-based general degradation model combining the Wiener process, Gamma process, and inverse Gaussian process is adopted to describe component degradation processes, and the factor analysis is employed to characterize the degradation interactions by seeking the latent common factors that dominate their interdependency. Thus the assumption of the identical degradation process and preset dependency structure can be relaxed, which enhances the robustness of the method. On this basis, we derive the explicit form of the system reliability function. An efficient expectation-maximization algorithm is then utilized for statistical inference to enable a fast computation. Finally, the superiority of the proposed method is demonstrated by two real case studies on lithium-ion battery packs.
We propose a hidden Markov model for multivariate continuous longitudinal responses with covariates that accounts for three different types of missing pattern: (I) partially missing outcomes at a given time occasion, ...
详细信息
We propose a hidden Markov model for multivariate continuous longitudinal responses with covariates that accounts for three different types of missing pattern: (I) partially missing outcomes at a given time occasion, (II) completely missing outcomes at a given time occasion (intermittent pattern), and (III) dropout before the end of the period of observation (monotone pattern). The missing-at-random (MAR) assumption is formulated to deal with the first two types of missingness, while to account for the informative dropout, we rely on an extra absorbing state. Estimation of the model parameters is based on the maximum likelihood method that is implemented by an expectation-maximization (EM) algorithm relying on suitable recursions. The proposal is illustrated by a Monte Carlo simulation study and an application based on historical data on primary biliary cholangitis.
Multiple-snapshot maximum-likelihood (ML) direction of arrival (DOA) estimation problem is studied for the intermittent jamming scenario. The intermittent jamming modality is based on the assumption that only a subset...
详细信息
Multiple-snapshot maximum-likelihood (ML) direction of arrival (DOA) estimation problem is studied for the intermittent jamming scenario. The intermittent jamming modality is based on the assumption that only a subset of the collected snapshots are contaminated by the jammer while the others are jammer free;but the receiver does not know which is which. This type of jamming is frequently encountered in practice either inadvertently, say due to the sporadic activity of a non-hostile system;or intentionally, say due to the activity of an adversary sweeping the operational bandwidth of the receiver. Exact maximum likelihood solution for the problem is analytically intractable and an expectationmaximization (EM) method based solution is developed for coherent and non-coherent signal models. Coherent signal model assumes that the phase difference between the coefficients of two consecutive snapshots are known a-priori which is an assumption compatible with the Swerling-1/3 target models in the radar signal processing literature. Non-coherent signal model does not have such an assumption and it is suitable for Swerling-2/4 targets. The suggested EM based solution is shown to yield an important estimation accuracy improvement over conventional maximum-likelihood solution which ignores the intermittency of jammer and also over the atomic norm based high resolution estimation techniques. Cramer-Rao type performance lower bounds for the problem is also provided to illustrate the efficacy of the suggested estimator. (C) 2021 Elsevier Inc. All rights reserved.
In this paper, a frequency domain expectation-maximization (EM)-based channel estimation algorithm for Space Time Block Coded-Orthogonal Frequency Division Multiplexing (STBC-OFDM) systems is investigated to support h...
详细信息
In this paper, a frequency domain expectation-maximization (EM)-based channel estimation algorithm for Space Time Block Coded-Orthogonal Frequency Division Multiplexing (STBC-OFDM) systems is investigated to support higher data rate applications in wireless communications. The computational complexity of the frequency domain EM-based channel estimation is increased when higher order constellations are used because of the ascending size of the search set space. Thus, a search set reduction algorithm is proposed to decrease the complexity without sacrificing the system performance. The performance results of the proposed algorithm is obtained in terms of Bit Error Rate (BER) and Mean Square Error (MSE) for 16QAM and 64QAM modulation schemes.
We consider the estimation of a distribution function when observations from this distribution are contaminated by measurement error. The unknown distribution is modeled as a mixture of a finite number of known distri...
详细信息
We consider the estimation of a distribution function when observations from this distribution are contaminated by measurement error. The unknown distribution is modeled as a mixture of a finite number of known distributions. Model parameters can be estimated and confidence intervals constructed using well-known likelihood theory. We show that it is also possible to apply this approach to estimation of a unimodal distribution. An application is presented using data from a dietary survey. Simulation results are given to indicate the performance of the estimators and the confidence interval procedures. [ABSTRACT FROM AUTHOR]
The Hawkes self-exciting model has become one of the most popular point-process models in many research areas in the natural and social sciences because of its capacity for investigating the clustering effect and posi...
详细信息
The Hawkes self-exciting model has become one of the most popular point-process models in many research areas in the natural and social sciences because of its capacity for investigating the clustering effect and positive interactions among individual events/particles. This article discusses a general nonparametric framework for the estimation, extensions, and post-estimation diagnostics of Hawkes models, in which we use the kernel functions as the basic smoothing tool.
Effective air quality management and forecasting in Beijing is urgently needed as the region suffers from the worst air pollution in any standards. However, the statistical mechanism of the PM(2.5)formation with respe...
详细信息
Effective air quality management and forecasting in Beijing is urgently needed as the region suffers from the worst air pollution in any standards. However, the statistical mechanism of the PM(2.5)formation with respect to various factors is underexplored in this region and China in general. Through an elaborate application with refinement of a spatio-temporal model with varying coefficients to the dynamics of PM(2.5)around Beijing based on a large dataset, we provide a comprehensive interpretation for the dynamics of PM(2.5)concentration with respect to its gaseous precursors, meteorological conditions and geographical variables. Furthermore, we conduct multistep temporal forecasts on a rolling basis for both the PM(2.5)concentration and the pollution levels. With the help of the expectation-maximization algorithm, the proposed models estimated for eight seasons from March 2015 to February 2017 around Beijing provide satisfactory in-sample fits and generate more accurate out-of-sample forecasts, compared with Finazzi and Fasso's original model as well as other alternative models. Valuable insights in tackling the excessive air pollution in Beijing are suggested from the comprehensive application of our model.
Robust design techniques, which are based on the concept of building quality into products or processes, are increasingly popular in many manufacturing industries. In this paper, we propose a new robust design model i...
详细信息
Robust design techniques, which are based on the concept of building quality into products or processes, are increasingly popular in many manufacturing industries. In this paper, we propose a new robust design model in the context of pharmaceutical production research and development. Traditional robust design principles have often been applied to situations in which the quality characteristics of interest are typically time insensitive. In pharmaceutical manufacturing processes, time-oriented quality characteristics, such as the degradation of a drug, are often of interest. As a result, current robust design models for quality improvement which have been studied in the literature may not be effective in finding robust design solutions. To address such practical needs, this paper develops a robust design model using censored data, which is perhaps the first attempt in the robust design field. We then study estimation methods, such as the expectation-maximization algorithm and the maximum likelihood method, in the robust design context. Finally, comparative studies are discussed for model verification via a numerical example.
Based on expectation-maximization algorithm, parameter estimation was proposed for data-driven nonlinear models in this work. On this basis, particle filters were used to approximately calculate integrals, deriving EM...
详细信息
Based on expectation-maximization algorithm, parameter estimation was proposed for data-driven nonlinear models in this work. On this basis, particle filters were used to approximately calculate integrals, deriving EM algorithm based on particle filter. And the effectiveness of using the proposed algorithm for the soft sensor of CO x content in tail gas of PX oxidation side reactions was verified through simulation results.
Transmission disequilibrium test (TDT) is a popular family based genetic association method. Under multiplicative assumption, a conditional logistic regression for matched pair, affected offspring with allele transmit...
详细信息
Transmission disequilibrium test (TDT) is a popular family based genetic association method. Under multiplicative assumption, a conditional logistic regression for matched pair, affected offspring with allele transmitted from parents and pseudo-offspring (control) with allele non-transmitted from parents, was built to detect the main effects of genes and gene-covariate interactions. When there exist genotype uncertainties, expectation-maximization (EM) algorithm was adopted to estimate the coefficients. The transmission model was applied to detect the association between M235T polymorphism in AGT gene and essential hypertension (ESH). Most of parents are not available in the 126 families from HongKong Chinese population. The results showed M235T is associated with hypertension and there is interaction between M235T and the case’s sex. The allele T is higher risk for male than female.
暂无评论