采用ZnO灭磁时阀片均流/均能的探讨

从ZnO电阻的非线性特性出发,对采用ZnO作为灭磁电阻时阀片的均流/均能进行理论论述,指出阀片均能性能的好坏主要依赖于阀片自身的特性;分析比较了ZnO阀片的不同选择方法对均流/均能的影响,指出阀片的均流/均能很大程度上取决于可供选择的阀片的库存量.该研究为发电机励磁系统的安全稳定运行提供了有力的保证.     

Nonlinear filtering structure for image smoothing in mixed-noise environments

This paper introduces a new nonlinear filtering structure for filtering image data that have been corrupted by both impulsive and nonimpulsive additive noise. Like other nonlinear filters, the proposed filtering structure uses order-statistic operations to remove the effects of the impulsive noise. Unlike other filters, however, nonimpulsive noise is smoothed by using a maximum a posteriori estimation criterion. The prior model for the image is a novel Markov random-field model that models image edges so that they are accurately estimated while additive Gaussian noise is smoothed. The Markov random-field-based prior is chosen such that the filter has desirable analytical and computational properties. The estimate of the signal value is obtained at the unique minimum of the a posteriori log likelihood function. This function is convex so that the output of the filter can be easily computed by using either digital or analog computational methods. The effects of the various parameters of the model will be discussed, and the choice of the predetection order statistic filter will also be examined. Example outputs under various noise conditions will be given.     

共轭高分子三阶非线性光学材料

概述了ｎ－共轭高分子材料的三阶非线性光学性质，着重讨论了化学结构对其光学非线性的影响，说明了ｎ－共轭聚合物的三阶非线性极化率主要取决于共轭主链的结构，侧链取代基的变化对其非线性影响不大，文中展望了共轭高分子材料在集成光学中的应用前景。     

激光光束质量因子的研究进展

本文详细分析了各种光场下光束质量M2因子。在不同的场中,A.E.Siegman当初所定义的M2因子,已经有了很大的变化,因而M2因子的特性也与当初不同,不仅M2因子可以大于等于1,而且可以小于1,甚至小于0。其反映的物理意义,也从经典场中的衍射极限倍数,变化为非经典场中的准直性量度以及对空间相干性的某些反映。此外还列举并分析了几种特殊的光束质量因子,最后讨论了M2因子应用的问题并指出了其局限性。     

螺旋弹簧的非线性理论及实验研究

本文通过对经典的圆柱螺旋弹簧理论的修正,给出了非线性理论解析公式.还通过对螺旋弹簧的精确测量和处理,验证了本文的非线性理论.     

Applications of Soliton Transmission Control in Optimal Design of Long－Haul Soliton Communication System

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Identification environment and robust forecasting for nonlinear time series

In this paper, the methods of time series for nonlinearity are briefly surveyed, with particular attention paid to a new test design based on a neural network specification. The proposed integrated expert system contains two main components: an identification environment and a robust forecasting design. The identification environment can be viewed as a integrated dynamic design in which cognitive capabilities arise as a direct consequence of their self-organizational properties. The integrated framework used for discussing the similarities and differences in the nonlinear time series behavior is presented. Moreover, its performance in prediction proves to be superior than the former work. For the investigation of robust forecasting, we perform a simulation study to demonstrate the applicability and the forecasting performance.     

A globally stable discrete-time controller for current-fed induction motors

In this short paper we present a discrete-time field oriented controller (FOC) for current-fed induction motors which insures global asymptotic speed regulation as well as rotor flux norm tracking. To the best of our knowledge, this is the first time such a result is rigorously established for a controller implemented in discrete-time. To insure global stability a condition on the reference for the rotor flux norm, which is time-varying, is imposed. This condition disappears as the sampling period goes to zero, hence allowing for independent speed regulation and rotor flux norm tracking. One important feature of our scheme is that, compared with the first-difference approximation of the classical indirect FOC, the additional computational burden is negligible. It is also shown that the result can easily be extended to the case of tracking time-varying references in speed or position.     

Identification of delayed system using instrumental variable method

System identification uses system inputs and outputs to raise mathematical models.Various techniques of system identification exist that offer a nominal model and an uncertainty bound.Many practical systems such as thermal processes & chemical processes have inbuilt time delay.If the time delay used in the system model for controller design does not concur with the actual process time delay,a closed-loop system may be unstable or demonstrate unacceptable transient response characteristics so here the time delay is assumed to be time-invariant. This paper proposes on-line identification of delayed complex/uncertain systems using instrumental variable(Ⅳ) method.Parametric uncertainty has been considered which may be represented by variations of certain system parameters over some possible range.This method allows consistent estimation when the system parameters are associated with the noise terms,as the IV methods(IVM’s)usually make no assumption on the noise correlation configuration.The faster convergence of the parameters including noise terms has been proved in this paper.Iterative prefiltering(IP)method has also been used for the identification of the delayed uncertain system and the graphical results given in this paper demonstrate that the convergence results are inferior to the instrumental variable method.     

基于多模型半参数非线性回归模型的外弹道节省参数估计

双星定位系统的应用是外弹道估计中的一种发展趋势。文章给出基于双星、光雷的联合测量模型,建立基于半参数回归的外弹道节省参数估计模型;给出基于半参数回归的外弹道节省参数估计算法及计算步骤,并从理论上分析了基于半参数回归的外弹道节省参数估计算法能有效地消除非线性因素对参数估计性能的影响,其估计精度优于经典的节省参数建模方法,并通过仿真得到：该算法确实有效。