System identification techniques based on support vector machines without bias term

The intention of this article is to utilize support vector machines (SVMs) as process models, which are the basis for most controller designs as well as simulation and monitoring tasks. SVMs are data‐driven models comparable with regularization networks, which merge elements from robust statistics, statistical learning, and kernel theory. The presentation is focused on the ‘no‐bias‐term’ variant, accounts for several peculiarities specific to SVM regression and derives an active‐set algorithm to solve the resulting large‐scale quadratic programming problem. For linear systems, SVMs are combined with multi‐stage methods for estimating output error and ARMAX models. Finally, two real‐world processes serve as test cases to evaluate the SVMs’ properties as nonlinear dynamic models. Copyright © 2013 John Wiley & Sons, Ltd.     

Dynamic spatial Bayesian models for radioactivity deposition

Dynamic spatial Bayesian (DSB) models are proposed for the analytical modelling of radioactivity deposition after a nuclear accident. The proposed models are extensions of the multi‐variate time‐series dynamic linear models of West and Harrison (1997) to Markov random field processes. They combine the outputs from a long‐range atmospheric dispersal model with measured data (and prior information) to provide improved deposition prediction in space and time. Two versions of a Gaussian DSB model were applied to the radioactivity deposition in Bavaria over a 15 days period during the Chernobyl nuclear accident. One version had fixed functional forms for its spatial variances and covariances while the other allowed those to adapt and ‘learn’ from data in the conjugate Bayesian paradigm. There were two main sources of information for radioactivity deposition in our application: radioactivity measurements at a sparse set of 13 monitoring stations, and the numerical deposition evaluation of the atmospheric dispersal K‐model for the points of a 64 × 64 regular grid. We have analysed the temporal predictions (one‐step‐ahead forecasting) of those DSB models to show that the dispersal K‐model tended in general to underestimate the deposition levels at all times while the DSB models corrected for that although with different degrees of adjustment.     

Must psychologists change the way they analyze their data?

Wagenmakers, Wetzels, Borsboom, and van der Maas (2011) argued that psychologists should replace the familiar “frequentist” statistical analyses of their data with Bayesian analyses. To illustrate their argument, they reanalyzed a set of psi experiments published recently in this journal by Bem (2011), maintaining that, contrary to his conclusion, his data do not yield evidence in favor of the psi hypothesis. We argue that they have incorrectly selected an unrealistic prior distribution for their analysis and that a Bayesian analysis using a more reasonable distribution yields strong evidence in favor of the psi hypothesis. More generally, we argue that there are advantages to Bayesian analyses that merit their increased use in the future. However, as Wagenmakers et al.'s analysis inadvertently revealed, they contain hidden traps that must be better understood before being more widely substituted for the familiar frequentist analyses currently employed by most research psychologists. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

A meta-analytic investigation of the structure of posttraumatic stress disorder symptoms.

Converging lines of evidence have called into question the validity of conceptualizations of posttraumatic stress disorder (PTSD) based on the Diagnostic and Statistical Manual of Mental Disorders (DSM; American Psychiatric Association, 2000) and suggested alternative structural models of PTSD symptomatology. We conducted a meta-analysis of 40 PTSD studies (N = 14,827 participants across studies) that used a DSM-based measure to assess PTSD severity. We aggregated correlation matrices across studies and then applied confirmatory factor analysis to the aggregated matrices to test the fit of competing models of PTSD symptomatology that have gained support in the literature. Results indicated that both prominent 4-factor models of PTSD symptomatology yielded good model fit across subsamples of studies; however, the model comprising Intrusions, Avoidance, Hyperarousal, and Dysphoria factors appeared to fit better across studies. Results also indicated that the best fitting models were not moderated by measure or sample type. Results are discussed in the context of structural models of PTSD and implications for the diagnostic nosology. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Fourier Analysis of Serial Dependence Measures

Classical spectral analysis is based on the discrete Fourier transform of the autocovariances. In this article we investigate the asymptotic properties of new frequency‐domain methods where the autocovariances in the spectral density are replaced by alternative dependence measures that can be estimated by U‐statistics. An interesting example is given by Kendall's τ, for which the limiting variance exhibits a surprising behavior.     

试析煤炭企业生产计划管理中面临的问题及解决对策

从树立管理观念、提高经营认知和健全节约机制等策略入手，对煤炭企业生产计划管理工作进行深入探析。     

Performance tradeoffs among low‐complexity detection algorithms for MIMO‐LTE receivers

The upcoming Third‐Generation Partnership Project—Long‐Term Evolution (3GPP‐LTE) cellular standard will employ spatial multiplexing to significantly increase the data rates. Detection of the spatially multiplexed signals is an essential issue in the design of an LTE receiver. In this paper, we evaluate the performance–complexity tradeoffs for a set of low‐complexity multiple input multiple output (MIMO) detection algorithms in a realistic LTE downlink system. Specifically, antenna correlation and channel estimation errors have been considered for a practical MIMO‐LTE receiver. An LTE downlink model has been implemented in order to evaluate three types of detectors: linear, unsorted successive interference cancellation (SIC), and ordered SIC. Our simulation results show that the unsorted SIC detectors present a very poor performance–complexity tradeoff. Besides, linear detectors are shown to be the best candidates as the performance improvement for the ordered SIC detectors is not significant in a realistic scenario. Copyright © 2009 John Wiley & Sons, Ltd.     

源岩C_4—C_7轻烃分析方法及其应用

本文介绍了源岩中轻烃的He抽提方法并直接与色谱联用分析其C_4～C_7轻烃。C_4～C_7轻烃在地球化学上有广泛的应用前景,文中以四川盆地两种不同来源的凝析油为例,讨论了利用这类烃来判断其母质来源、成熟度和气源对比。     

母体均值和标准差的稳健估计

本文先给出单项数列估计母体参数的几个稳健方法，再将它们推广到分组数据的情形。     

随机向量的逼近及奇异值分隔定理的应用

Ｃ．Ｒ．Ｒａｏ在［１］中都是在协方差矩阵为非奇异的情况下讨论的，作者把它们都推广到奇异的情形．作者在讨论用一个随机向且通过一个已知的随机向量中也得出一些结果，并肯定了Ｃ．Ｒ．Ｒａｏ的一个猜测．