基于小波算法的二阶线性定常分布参数系统的辨识

本文基于正交函数逼近方法,借助于小波变换,并利用其运算矩阵及其运算性质,研究了分布参数系统的辨识问题。将Haar小波正交基应用于分布参数系统的辨识中,经正交小波逼近变换,将原偏微分描述的分布参数系统转化为代数矩阵方程,并且,考虑了初始条件和边界条件,获得了算法简单、计算方便、具有较高精度的辨识算法,简化了分布参数系统辨识的求解过程,应用在分布参数系统辨识中不失为一种有效的分析方法。仿真实例表明了本文所提出的算法的有效性。     

测量散射参数的交互换位双信号方法及其应用

叙述了外内向功率波复数比的测量方法,给出了散射参数测量的交互换位双信号测量线方法。用此方法测量了双栅ＧａＡｓＭＥＳＦＥＴ适用散射参数,并用它设计Ｓ波段混合集成双栅ＧａＡｓＭＥＳＦＥＴ可控增益放大器。测试结果与设计吻合。     

机械图参数化绘图通用AutoLISP函数设计与应用

介绍在AutoCAD环境下,用AutoLISP语言开发机械图参数化绘图通用函数方法．提出了尺寸公差表输入方式的自动判别模式．函数的建立,可提高编程效率,缩短软件开发周期。程序已在AutoCAD10.0版上运行通过,并应用于换热器CAD项目中,取得了较好的经济效益．     

Enhanced locality preserving projections using robust path based similarity

Curse of dimensionality is a bothering problem in high dimensional data analysis. To enhance the performances of classification or clustering on these data, their dimensionalities should be reduced beforehand. Locality Preserving Projections (LPP) is a widely used linear dimensionality reduction method. It seeks a subspace in which the neighborhood graph structure of samples is preserved. However, like most dimensionality reduction methods based on graph embedding, LPP is sensitive to noise and outliers, and its effectiveness depends on choosing suitable parameters for constructing the neighborhood graph. Unfortunately, it is difficult to choose effective parameters for LPP. To address these problems, we propose an Enhanced LPP (ELPP) using a similarity metric based on robust path and a Semi-supervised ELPP (SELPP) with pairwise constraints. In comparison with original LPP, our methods are not only robust to noise and outliers, but also less sensitive to parameters selection. Besides, SELPP makes use of pairwise constraints more efficiently than other comparing methods. Experimental results on real world face databases confirm their effectiveness.     

基于移动网核心侧与无线侧参数合理配置的研究

合理设置、调整核心网、无线网参数是提高GSM网络整体性能的必要手段。随着GSM网络优化工作的深入开展,核心网的参数设置对全网用户接入、寻呼、增值业务使用等方面的广泛影响而日渐得到重视;无线网参数对网络中小区的覆盖、信令流程的分布、网络的业务性能等也具有至关重要的影响;同时周期性位置更新、隐含用户关机等参数,必须核心网与无线网的定时器、参数值关联设置才能起到良好的作用。本文结合多年网络优化经验,对核心网、无线网关键参数的合理设置及调整,逐一进行阐述。     

迭代函数系IFS吸引子的参数控制与树木的模拟

文章讨论了迭代函数系ＩＦＳ吸引子的参数控制,讨论了ＩＦＳ参数控制实现模拟树木的方法。     

Identification schemes for unmanned excavator arm parameters

Parameter identification is a key requirement in the field of automated control of unmanned excavators （UEs）. Furthermore, the UE operates in unstructured, often hazardous environments, and requires a robust parameter identification scheme for field applications. This paper presents the results of a research study on parameter identification for UE. Three identification methods, the Newton-Raphson method, the generalized Newton method, and the least squares method are used and compared for prediction accuracy, robustness to noise and computational speed. The techniques are used to identify the link parameters （mass, inertia, and length） and friction coefficients of the full-scale UE. Using experimental data from a full-scale field UE, the values of link parameters and the friction coefficient are identified. Some of the identified parameters are compared with measured physical values. Furthermore, the joint torques and positions computed by the proposed model using the identified parameters are validated against measured data. The comparison shows that both the Newton-Raphson method and the generalized Newton method are better in terms of prediction accuracy. The Newton-Raphson method is computationally efficient and has potential for real time application, but the generalized Newton method is slightly more robust to measurement noise. The experimental data were obtained in collaboration with QinetiQ Ltd.     

Computer-aided design integration of a reinforced vibration isolator for electronic equipment’s system basedon experimental investigation

Electronic equipment’s system is always manufactured as a superprecision system. However, it will be used in harsh environment. For example, the computer in moving vehicles will be acted by vibrations. The objective of this paper is to provide a systematic investigation to test and computer-aided design of the vibration isolator for protection of electronic equipment’s system in harsh vibration environment. A micro-oil damping vibration isolator is designed and manufactured through coupling the oil and spring by ingenious tactics. The structure of the oil damping vibration isolator can achieve circulating oil damping function with an inner tube and an outer tube (some orifices are manufactured on upside and underside of the inner tube). The dynamics of the key model machine is systematically investigated. Based on the test, a nonlinear dynamic model for the vibration isolator is presented by analyzing the internal fluid dynamic phenomenon with respect to the vibration isolator. The model considers all the physical parameters of the structure. Comparisons with experimental data confirm the validity of the model. In the other, the model is integrated by introducing normalization measure. The normalization model shows the actual physical characteristics of the oil damping vibration isolator by considering quadratic damping, viscous damping, Coulomb damping, and nonlinear spring forces. An approximate solution is deduced by introducing harmonic transform method and Fourier transform method. Therefore, a parameter-matching optimal model for computer-aided design of the vibration isolator is build based on approximate solution. An example confirms the validity of the computer-aided design integration.

基于LTCC技术射频传输线的设计

本文介绍了射频传输线及LTCC技术的概念和特点,建立了基于LTCC技术的射频传输线模型,推导了传输线模型特征参数提取公式;并对传输线模型进行三维电磁仿真,得到了仿真参数。通过分析传输线性能,提出了优化设计的一定方法     

人工神经网络在注塑参数预测中的应用

应用人工神经网络技术建立了注塑工艺参数值快速预测的双层BP网络模型。利用CAE软件进行模拟，获取训练样本。用Matlab语言编制了应用程序，对网络的训练及参数预测的过程进行求解。将网络预测结果与模拟所得验证数据进行比较和误差分析，显示出BP网络的稳定性和可靠性。经实例验证，表明人工神经网络技术应用于注塑参数值的快速预测和选取方面是可行的。