350m~3高炉煤气净化单文氏管可调喉口理论计算及分析

通过单文氏管可调喉口的理论计算及分析，找出喉口最佳工作状态下的工艺参数及适合这种设备特性的煤气工作参被变化范围，以期能对实际操作过程及运行状态分析提供理论依据，提出单文氏可调喉口在更广泛意义上的设备、工艺参数选择、计算的方法。     

非正态随机变量的可靠性评价方法研究

不确定性及可靠性分析技术已广泛应用到水利及土木系统工程分析中，可靠性计算的核心之一是对随机变量进行正态转换。文中旨在对土木工程系统不确定性及可靠性分析中有着潜在应用前景的非正态随机变量的多项式正态转换方法进行研究。通过在各种条件下非正态随机变量的正态多项式转换成果之评价，发现在水利及土木工程系统可靠性分析中常用的许多分布可以保留其自身的比较好的特征。     

Beyond Wiener–Askey Expansions: Handling Arbitrary PDFs

In this paper we present a Multi-Element generalized Polynomial Chaos (ME-gPC) method to deal with stochastic inputs with arbitrary probability measures. Based on the decomposition of the random space of the stochastic inputs, we construct numerically a set of orthogonal polynomials with respect to a conditional probability density function (PDF) in each element and subsequently implement generalized Polynomial Chaos (gPC) locally. Numerical examples show that ME-gPC exhibits both p- and h-convergence for arbitrary probability measures     

Genetically optimized fuzzy polynomial neural networks with fuzzy set-based polynomial neurons

In this paper, we propose and investigate a new category of neurofuzzy networks—fuzzy polynomial neural networks (FPNN) endowed with fuzzy set-based polynomial neurons (FSPNs) We develop a comprehensive design methodology involving mechanisms of genetic optimization, and genetic algorithms (GAs) in particular. The conventional FPNNs developed so far are based on the mechanisms of self-organization, fuzzy neurocomputing, and evolutionary optimization. The design of the network exploits the FSPNs as well as the extended group method of data handling (GMDH). Let us stress that in the previous development strategies some essential parameters of the networks (such as the number of input variables, the order of the polynomial, the number of membership functions, and a collection of the specific subset of input variables) being available within the network are provided by the designer in advance and kept fixed throughout the overall development process. This restriction may hamper a possibility of developing an optimal architecture of the model. The design proposed in this study addresses this issue. The augmented and genetically developed FPNN (gFPNN) results in a structurally optimized structure and comes with a higher level of flexibility in comparison to the one we encounter in the conventional FPNNs. The GA-based design procedure being applied at each layer of the FPNN leads to the selection of the most suitable nodes (or FSPNs) available within the FPNN. In the sequel, two general optimization mechanisms are explored. First, the structural optimization is realized via GAs whereas the ensuing detailed parametric optimization is carried out in the setting of a standard least square method-based learning. The performance of the gFPNN is quantified through experimentation in which we use a number of modeling benchmarks—synthetic and experimental data being commonly used in fuzzy or neurofuzzy modeling. The obtained results demonstrate the superiority of the proposed networks over the models existing in the references.     

奇异值分解压制随机噪声的方法及应用

针对随机噪声压制问题，通过对多项式确定的同相轴形状重新选取数据矩阵，再对新选取的数据矩阵进行SVD滤波，从而压制随机噪声。通过对矩阵奇异值分解的研究，揭示了奇异值分解的原理和SVD滤波原理，将一个多道地震记录看作一个图，它可分解为由一系列正交的子图，通过对子图适当选择并结合其它手段，从而达到提高信噪比的目的，为奇异值分解在地球物理中的进一步应用提供了理论依据。实际数据应用表明，该方法去噪手段灵活、保真性好、分辨率高，对一些突然的脉冲干扰、侧反射、以及其他的反向干扰有明显效果。     

Spectral color reproduction minimizing spectral and perceptual color differences

In this article, we are combining minimization criteria in the colorant separation process for spectral color reproduction. The colorant separation is performed by inverting a spectral printer model: the spectral Yule‐Nielsen modified Neugebauer model. The inversion of the spectral printer model is an optimization operation in which a criterion is minimized at each iteration. The approach we proposed minimizes a criterion defined by the weighted sum of a spectral difference and a perceptual color difference. The weights can be tuned with a parameter α ∞ [0, 1]. Our goal is to decrease the spectral difference between the original data and its reproduction and also to consider perceptual color difference under different illuminant conditions. In order to find the best α value, we initially compare a pure colorimetric criterion and a pure spectral criterion for the reproduction, then we combine them. We perform four colorant separations: the first separation will minimize the 1976 CIELAB color difference where four illuminants are tested, the second separation will minimize an equally weighted summation of 1976 CIELAB color difference with the four illuminants tested independently, the third colorant separation will minimize a spectral difference, and the fourth colorant separation will combine a weighted sum of a spectral difference and one of the two first colorimetric differences previously introduced. This last colorant separation can be tuned with a parameter in order to emphasize on spectral or colorimetric difference. We use a six colorants printer with artificial inks for our experiments. The prints are simulated by the spectral Yule‐Nielsen modified Neugebauer model. Two groups of data are used for our experiments. The first group describes the data printed by our printing system, which is represented by a regular grid in colorant space of the printer and the second group describes the data which is not originally produced by our printing system but mapped to the spectral printer gamut. The Esser test chart and the Macbeth Color Checker test chart have been selected for the second group. Spectral gamut mapping of this data is carried out before performing colorant separation. Our results show improvement for the colorant separations combining a sum of 1976 CIELAB color difference for a set of illuminants and for the colorant separation combining a sum of 1976 CIELAB color difference and spectral difference, especially in the case of spectral data originally produced by the printer. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 494–504, 2008     

Perceptual evaluation of color gamut mapping algorithms

The recommendation of the CIE has been followed as closely as possible to evaluate the accuracy of five color gamut mapping algorithms (GMAs)—two nonspatial and three spatial algorithms—by psychophysical experiments with 20 test images, 20 observers, one test done on paper and a second one on display. Even though the results do not show any overall “winner,” one GMA is definitely perceived as not accurate. The importance of a high number of test images to obtain robust evaluation is underlined by the high variability of the results depending on the test images. Significant correlations between the percentage of out‐of‐gamut pixels, the number of distinguishable pairs of GMAs, and the perceived difficulty to distinguish them have been found. The type of observers is also important. The experts, who prefer a spatial GMA, show a stronger consensus and look especially for a good rendering of details, whereas the nonexperts hardly make a difference between the GMAs. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 470–476, 2008     

数字电视显示图像的同心度、重显率和过扫描

讨论了数字电视显示图像的同心度、重显率和过扫描，描述了它们的测量方法，重点分析了它们之间的内在联系，以及用它们来衡量显示图像质量的优缺点。实测表明，正确调整和测定这些指标，对保证数字电视图像主观效果具有重要作用。     

基于Legendre多项式的随机连续系统的Markov参数估计

本文在讨论连续Ｗｉｓｅｎｒ过程的Ｌｅｇｅｎｄｒｅ多项式逼近值的相关性和Ｗｉｅｎｅｒ过程扰动下连续线性系统基于该正交多项的最小二乘估计有偏性后，提出了无偏一致的且数估计误差方差最小的Ｍａｒｋｏｖ估计（最小方差估计）算法，并给出本文方法的仿真结果。