Nonlinear adaptive algorithms for equalisation in mobile satellite communications

This paper considers the equalisation problem in Quadrature Phase-Shift Keying (QPSK) modulated signals which have been distorted by the passage through a transmission channel. The channel is modelled as a Rician fading channel to simulate the behaviour of the transmission channel in the mobile satellite context. The equalisation is treated as the generalisation of the channel behaviour, and some algorithms with the structure of an artificial neural network using the Multilayer Perceptron, Volterra Series and Radial Basis Function are described. Results for the BER performance of typical transversal equalisers, with Square-Root Kalman adaptation algorithm, and algorithms with artificial neural network structure are also reported and evaluated. Improved performance is exhibited by the artificial neural network approaches.     

On parity problems and the functional-link artificial neural network

This paper contains the proof of a theorem on the capability of functional-link artificial neural networks both to represent and to learn the n-dimensional parity problem. The result is obtained by an embedding of the problem into a space of dimension 2ⁿ — 1. It is shown that the Volterra expansion of the data in n-dimensions provides the necessary transformation. By computing the parity function, it is shown that a suitable set of neural network weights can be deduced. Finally, it is demonstrated that 2ⁿ — 1 is the minimum embedding dimension for the problem.The contribution of A Zuderell of the University of Innsbruck is acknowledged.     

A NEW ALGORITHM FOR ADAPTIVE LATTICE FILTERAND ITS APPLICATION IN THE SPEECH LINEARPREDICTIVE SYNTHESIS

In this paper, an adaptive line spectral pair filter is derived from an adaptive lattice filter. A least-mean-square(LMS) type adaptive algorithm used to calculate directly the line spectral pair(LSP) coefficients on a stage-by-stage basis is presented. Experimental results show that the algorithm has higher convergence rate and lower misadjustment as compared with the other algorithms. The LSP coefficients calculated by the algorithm have been used to carry out speech linear predictive synthesis, resulting in better results than PARCOR coefficients.     

An evaluation system of the setting up of predictive maintenance programmes

Predictive Maintenance can provide an increase in safety, quality and availability in industrial plants. However, the setting up of a Predictive Maintenance Programme is a strategic decision that until now has lacked analysis of questions related to its setting up, management and control. In this paper, an evaluation system is proposed that carries out the decision making in relation to the feasibility of the setting up. The evaluation system uses a combination of tools belonging to operational research such as: Analytic Hierarchy Process, decision rules and Bayesian tools. This system is a help tool available to the managers of Predictive Maintenance Programmes which can both increase the number of Predictive Maintenance Programmes set up and avoid the failure of these programmes. The Evaluation System has been tested in a petrochemical plant and in a food industry.     

X射线三轴晶衍射法测量半绝缘GaAs单晶的化学配比

采用X射线三轴晶衍射法,根据As间隙原子对作为过量As在GaAs单晶材料中存在的主要形式的模型,可以无损、高精度测量半绝缘GaAs单晶的化学配比.并探讨了引起晶格变化的原因及其与熔体组分的关系,对于制备高质量GaAs单晶及其光电器件具有重要的意义.     

基于物元分析和层次分析的选厂综合性能评估

利用物元分析法和层次分析法的特点，将物元分析和层次分析法有机的结合起来建立选厂性能综合评估模型，建立的评估模型表明该评估方法能够克服传统方法中参评人员的主观不确定性和认识上的模糊性，可用于选厂有关指标的综合评估。     

用模糊综合评判法评估钢制储罐的寿命

针对影响钢制储罐寿命的因素具有复杂性、非确定性以及时变性的特点,提出了用动态二级模糊综合评判的方法对其寿命进行评估,建立了评估的数学模型和评估流程。在对某石油库油罐的寿命分析中,考虑到保留所有评判因素的影响,采用了乘、加型模糊算子,并用层次分析法来确定评价指标权重。计算结果表明,该方法能够解决储罐寿命评估中的一些复杂因素的处理问题,具有一定的实际工程意义。     

非均匀材料破坏过程数值模拟的边界元法研究

用格子模型和统计分布模拟非均匀材料性质的初始分布,针对二维非均匀材料格子模型建立了重复多子域边界元法求解方程。通过把各行子域集成为亚子域,然后对链状排列的亚子域应用域转移矩阵法进行求解。由于使用的域转移矩阵法对内存的要求仅略大于一个亚子域的求解,以及重复多子域法只需要进行一次系数矩阵积分,因而可以大大提高求解的规模和效率。在此基础上,对非均匀脆性材料在简单载荷作用下的破坏过程进行了数值模拟。采用重复多子域法和域转移矩阵法,可以得到子域内高精度的连续应力分布,为进一步研究非均匀材料裂纹萌生、扩展和破坏过程提供了基础。     

A new method to cope with decision makers' uncertainty in the equipment selection process

One of the main problems faced while configuring or reconfiguring manufacturing systems is to rank alternative designs taking into account all the different aspects involved (both tangible and intangible). For this purpose the Analytic Hierarchy Process (AHP) is a well-known decision making support method that addresses this problem. A major drawback of AHP is that uncertainty in the judgments of the decision makers and the resulting impact on the ranking is not considered. In real situations, however, judgments based on perceived future scenarios are almost always uncertain. To solve this problem in this paper we present the first complete probabilistic extension to the AHP method. The new method provides the decision maker not only with information on the ranking of the alternatives but also the probability that the ranking remains stable even in presence of uncertainty in the judgements. We verified the validity of the new method in a real application developed for the Ferrari racing team.