Systematic convergence of nonlinear stochastic estimators on the Special Orthogonal Group SO(3)

This paper introduces two novel nonlinear stochastic attitude estimators developed on the Special Orthogonal Group with the tracking error of the normalized Euclidean distance meeting predefined transient and steady‐state characteristics. The tracking error is confined to initially start within a predetermined large set such that the transient performance is guaranteed to obey dynamically reducing boundaries and decrease smoothly and asymptotically to the origin in probability from almost any initial condition. The proposed estimators produce accurate attitude estimates with remarkable convergence properties using measurements obtained from low‐cost inertial measurement units. The estimators proposed in continuous form are complemented by their discrete versions for the implementation purposes. The simulation results illustrate the effectiveness and robustness of the proposed estimators against uncertain measurements and large initialization error, whether in continuous or discrete form.     

微制造平台微振动的最优控制

采用混合隔振技术建立了微制造平台隔振系统。该系统以空气弹簧和橡胶层作为被动隔振元件、超磁致伸缩致动器作为主动隔振元件，并采用最优控制理论设计其主动控制器。研究了在不同的性能指标加权阵的情况下，该主动振动控制系统对基础干扰和由微制造设备产生的直接干扰所引起的微制造平台振动的控制效果。研究表明性能指标加权阵对振动控制效果影响非常大。通过大量的仿真实验确定了一组性能指标加权阵，使所设计的主动控制系统能在较宽的频率范围对基础干扰和直接干扰所引起的微制造平台振动进行有效的控制。     

An original approximate method for estimating the invariant probability distribution of a large class of multi-dimensional nonlinear stochastic oscillators

This paper proposes an original method for obtaining analytical approximations of the invariant probability density function of multi-dimensional Hamiltonian dissipative dynamic systems under Gaussian white noise excitations, with linear non-conservative parts and nonlinear conservative parts. The method is based on an exact result and a heuristic argument. Its pertinence is attested by numerical tests.     

Characteristic Features of the Optimal Processing of the Results of Measurements in the Case of a Random Observation Function

An analysis is made of the characteristic features and problems of the optimal processing of the results of measurements in the case of a random observation function utilizing a nonlinear Kalman filter. A method is proposed for increasing the convergence domain of the filter with additional processing of measurements in the frequency domain.     

A stochastic model for localized disturbances and its applications

A stochastic model for local disturbances, particularly for a temporal harmonic with random modulations in amplitude and/or phase, is proposed in this paper. Results for the second moment responses of a linear single-degree-of-freedom system to this type of stochastic loading demonstrate a significant change in response characteristics due to a small uncertainty. A local phenomenon may last much longer and resonance may be smeared to a broad range. Integrated with wavelet transform, the proposed approach may be used to model a random process with non-stationary frequency content. Especially, it can be effectively used for Monte Carlo simulation to generate large size of samples that have similar characteristics in time and frequency domains as a pre-selected mother sample has. The technique has a great potential for the case where uncertainty study is warranted but the available samples are limited.     

弹性-粘弹性复合结构随机响应的各阶谱矩的计算方法

提出了一种新的计算弹性-粘弹性复合结构随机响应的各阶谱矩的计算方法，它是一种时域复模态分析方法。利用此方法获得了弹性-粘弹性复合结构在白噪声、滤过白噪声等典型平稳随机激励下随机响应的各阶谱矩的解析表达式，分析了粘弹性对各阶谱矩的影响。此计算方法简便、易用，无论单自由度或多自由度系统均适用，为进一步研究弹性-粘弹性复合结构在随机激励下的可靠性打下良好基础。     

一种实现最佳用户检测的非线性优化神经网络

本文提出并讨论了实现码分多址（CDMA）系统上最佳多用户检测（MUD）的一种神经网络方法。该方法通过将最佳多用户检测视为非线性优化组合问题，利用神经网络能有效求解非线性优化问题的优势，导出了一种非线性优化神经网络来实现最佳多用户检测，理论分析和计算机模拟表明，所提出的神经网络具有可实时应用的动态性能和较传统方法优越得多的误码率性能和抗多址干扰的性能。     

精细功能陶瓷的若干发展趋势

概括了分析自９０年代初以来精细功能陶瓷的发展趋势，提出了一些相关的研究领域。     

Image processing using cellular neural networks based on multi-valued and universal binary neurons

Multi-valued and universal binary neurons (MVN and UBN) are the neural processing elements with the complex-valued weights and high functionality. It is possible to implement an arbitrary mapping described by partially defined multiple-valued function on the single MVN. An arbitrary mapping described by partially defined or fully defined Boolean function, which can be non-threshold, may be implemented on the single UBN. The quickly converging learning algorithms exist for both types of neurons. Such features of the MVN and UBN may be used for solving the different problems. One of the most successful applications of the MVN and UBN is their usage as basic neurons in the Cellular Neural Networks (CNN). It opens the new effective opportunities in nonlinear image filtering and its applications to noise reduction, edge detection and solving of the super resolution problem. A number of experimental results are presented to illustrate the performance of the proposed algorithms.An erratum to this article can be found at     

挠性胶管的阻尼减振机理初探

建立了挠性胶管阻尼耗能的简化模型。以此为基础分析了挠性胶管的阻尼耗能的一般规律,并得出了一些新的结论。