Polynomial filtering for nonlinear stochastic systems with state‐ and disturbance‐dependent noises

This article is concerned with the polynomial filtering problem for a class of nonlinear stochastic systems governed by the Itô differential equation. The system under investigation involves polynomial nonlinearities, unknown‐but‐bounded disturbances, and state‐ and disturbance‐dependent noises ((x,d)‐dependent noises for short). By expanding the polynomial nonlinear functions in Taylor series around the state estimate, a new polynomial filter design method is developed with hope to reduce the conservatism of the existing results. In virtue of stochastic analysis and inequality technique, sufficient conditions in terms of parameter‐dependent linear matrix inequalities (PDLMIs) are derived to guarantee that the estimation error system is input‐to‐state stable in probability. Moreover, the desired polynomial matrix can be obtained by solving the PDLMIs via the sum‐of‐squares approach. The effectiveness and applicability of the proposed method are illustrated by two numerical examples with one concerning the permanent magnet synchronous motor.     

柴达木盆地三湖坳陷横波勘探中的低幅异常消除技术

近年来,在柴达木盆地三湖坳陷开展了横波地震勘探,但是由于该区低幅度构造发育,横波静校正引起的"低幅"异常与上述低幅度构造相互混杂,难以区分。为此,针对该区横波表层调查难以控制表层横波速度模型的变化、横波近偏移距初至污染严重、横波折射层发育导致高速界面难以确定等问题,首先采用曲线拟合技术预测污染区横波初至时间确保初至完整性,然后采用面波模型与多层折射分层联合约束反演横波表层速度,最后通过基于速度谱分析的层位匹配建模技术确定合理的横波速度界面,形成了横波表层"低幅"异常消除技术,并进行了现场应用及效果评价。研究结果表明:①曲线拟合技术可以弥补近道污染区横波初至空白,保证层析反演模型的完整性;②基于瑞雷波的频散特性反演建模可以为确定该区浅层横波速度提供可靠的资料,提高浅层模型精度;③面波模型与多层折射分层联合约束反演能够更准确的反演该区表层横波速度场,较好地建立横波速度模型,消除横波剖面上"低幅"异常现象。结论认为,所形成的横波地震勘探低幅异常消除技术消除了横波静校正引起的"低幅"异常现象,提高了横波地震资料的成像品质。     

A novel approach based on artificial neural network for calibration of multi-hole pressure probes

Imperfections in the manufacturing process of flow measuring probes affect their measuring behavior. Nevertheless, in order to provide the highest possible accuracy, each individual multi-hole pressure probe has to be calibrated before using them in turbomachinery. This paper presents a novel method based on artificial neural networks (ANN) to predict the flow parameters of multi-hole pressure probes. A two-stage ANN approach using multilayer perceptron (MLP) is proposed in this study. The two-stage prediction approach involves two MLP networks, which represent the calibration data and the prediction error. For a given set of inputs, outputs from both networks are combined to estimate the measured value. The calibration data of a 5-hole probe at RWTH Aachen was used to develop and validate the proposed ANN models and two-stage prediction approach. The results showed that the ANN can predict the flow parameters with high accuracy. Using the two-stage approach, the prediction accuracy was further improved compared to polynomial functions, i.e. a commonly used method in probe calibration. Furthermore, the proposed approach offers high interpolation capabilities while preventing overfitting (i.e. failure to fit new data). Unlike polynomials, it is shown that the ANN based method can provide accurate predictions at intermediate points without large oscillations.     

Prebiotic Pathway from Ribose to RNA Formation

At the focus of abiotic chemical reactions is the synthesis of ribose. No satisfactory explanation was provided as to the missing link between the prebiotic synthesis of ribose and prebiotic RNA (preRNA). Hydrogen cyanide (HCN) is assumed to have been the principal precursor in the prebiotic formation of aldopentoses in the formose reaction and in the synthesis of ribose. Ribose as the best fitting aldopentose became the exclusive sugar component of RNA. The elevated yield of ribose synthesis at higher temperatures and its protection from decomposition could have driven the polymerization of the ribose-phosphate backbone and the coupling of nucleobases to the backbone. RNA could have come into being without the involvement of nucleotide precursors. The first nucleoside monophosphate is likely to have appeared upon the hydrolysis of preRNA contributed by the presence of reactive 2′-OH moieties in the preRNA chain. As a result of phosphorylation, nucleoside monophosphates became nucleoside triphosphates, substrates for the selective synthesis of genRNA.     

Multilayer thermal object identification in frequency domain using IR thermography and vector fitting

This paper deals with the identification of the thermal parameters of multilayer objects using the concept of thermal impedance. In order to perform such identification, temperature evolution in time is obtained by an infrared camera after power excitation is applied in the investigated structure. Infrared thermography offers the advantage of being a noncontact temperature detection and measurement method. In many practical cases, it is impossible to use contact temperature measurements. Typically, the power in the form of a step function is applied. In order to calculate the thermal impedance of an object, temperature and power are converted into the frequency domain using the Laplace transform for s = jω. Then, the poles of the thermal impedance are identified using vector fitting, which allows calculating the thermal impedance as a sum of partial fractions. This corresponds directly to the Foster network of a thermal object. In addition, the vector fitting method offers much better convergence in comparison with other methods using the polynomial rational approximation of thermal impedance. A considerable improvement of the numerical Laplace transform in high frequency range is proposed. In this approach, the variable s = jω is replaced by , and then, the integration result is corrected by the Taylor series. It leads to a kind of filtering of the temperature signal.     

A continuous network location problem for a single refueling station on a tree

This article considers the continuous version of the refueling station location problem on a tree network, which is a common structure in numerous toll roads worldwide, so as to locate a single alternative-fuel refueling station to maximize the traffic flow covered in round trips/day. Two reduction properties regarding the problem size and some optimality conditions are derived. Based on these conditions, an exact polynomial algorithm is developed to determine the set of optimal locations for the refueling station. A small tree network example is solved to illustrate the algorithm.     

Elitist clonal selection algorithm for optimal choice of free knots in B-spline data fitting

Data fitting with B-splines is a challenging problem in reverse engineering for CAD/CAM, virtual reality, data visualization, and many other fields. It is well-known that the fitting improves greatly if knots are considered as free variables. This leads, however, to a very difficult multimodal and multivariate continuous nonlinear optimization problem, the so-called knot adjustment problem. In this context, the present paper introduces an adapted elitist clonal selection algorithm for automatic knot adjustment of B-spline curves. Given a set of noisy data points, our method determines the number and location of knots automatically in order to obtain an extremely accurate fitting of data. In addition, our method minimizes the number of parameters required for this task. Our approach performs very well and in a fully automatic way even for the cases of underlying functions requiring identical multiple knots, such as functions with discontinuities and cusps. To evaluate its performance, it has been applied to three challenging test functions, and results have been compared with those from other alternative methods based on AIS and genetic algorithms. Our experimental results show that our proposal outperforms previous approaches in terms of accuracy and flexibility. Some other issues such as the parameter tuning, the complexity of the algorithm, and the CPU runtime are also discussed.     

基于增强算子的污染土雷达图像特征提取仿真

针对雷达图像特征提取效率低、精度不高等问题,提出一种基于增强算子的污染土雷达图像特征提取方法。首先使用多尺度非均匀滤波把含有噪声与不含噪声的像素点灰度值、构成因素及像素加权灰度密度三个特征进行划分,完成雷达图像去噪。其次提出增强算子方法,将图像数据转变至图像的空间域,以此判断污染土雷达图像内是否存在对比度不高区域和细微区域。最后采用灰色关联分析计算超像素之间的相似度,运用MLS增强算子对曲面进行拟合,通过高斯曲率与平均曲率构建出特征判断准则,提高图像特征提取完整性,实现污染土雷达图像特征的精准提取。仿真结果表明,与传统方法相比所提方法计算速度较快,雷达特征提取效率较高,可大幅提升污染土雷达图像特征提取准确率。