Synthesizing the two identification methods of weighted least square and resricted memory , the mutivariable system recursive estimate algorithems of unknown parameter of autoregressive models in the presence of controlled inputare are given 摘要将加权最小二乘法和限定记忆两种参数估计方法相综合，给出了多变量系统带控制输入的自回归模型未知参数的递推估计算法。
About and of two normal distribution and of gamma distribution . when sample size is not large , conclusion shows that the precision of the interval estimation of parameter is remarkably increasing if the data from tables in this paper are used 通过计算比较，得出结论：在小样本的情况下，用本文所求的置信区间作为未知参数的区间估计将会使估计精度得到显著的提高。
The unknown parameters are estimated in the time domain . the global uniformly exactly tracking of the trajectory on the specified time interval is achieved and the boundedness of all signals of the closed - loop system is ensured 在时域中估计系统的未知参数，所提出的自适应迭代学习控制器在给定的区间上实现了对目标轨线的全局一致精确跟踪，同时保证了闭环系统所有信号全局一致有界。
The systems of 1 order , 2 order and 3 order , which keep one or two unknown parameters are researched by computer simulation , and the experiment results indicate that this method has extremely high sensitivity and resolution . at the same time , the applicable limits of the systems are also given 对一阶、二阶和三阶的，含有一个或二个未知参数的系统进行了计算机仿真研究，结果表明这种方法具有极高的灵敏度和分辨率，同时也对该方法的适用范围作了分析。
Compared with classical recursive extended least squares , their accuracy obviously is improved . applying these new algorithms to the parameter estimation problem for systems with measurement noises , some new approaches and algorithms of parameter estimation for system with measurement noises , are presented , for example , two - stage rels - gevers - wouters algorithm and three - stage rls - pi - gevers - wouters algorithm , which solve the biased parameter estimation problem by classical least squares method 并将这些算法推广到带观测噪声系统参数估计的问题，给出了带观测噪声系统参数估计的一些新方法和新算法，其中包括两段rels - gevers - wouters算法和三段rls - pi - gevers - wouters算法，解决了用普通最小二乘法估计带观测噪声系统未知参数的有偏问题。
An sm based identifier is presented to deal with the parameter identification problem for a class of parameter uncertain nonlinear dynamic systems with input nonlinearity . an smc algorithm is employed to ensure the global reaching condition of the sliding mode for the nonlinear system , and an identifier is designed to identify the uncertain parameters of the nonlinear system 论文的主要内容如下：针对一类相对于输入为非线性的系统，设计了滑模变结构控制器保证非线性系统的全局渐近稳定，在此基础上，考虑到系统运行在滑模面上时所具有的特点，提出了一种基于滑模变结构控制的参数辨识方法来辨识非线性系统的未知参数。
( 2 ) using the method of parameter identification in literature [ 117 - 118 ] , selecting gain function : giving the initial value of the parameter observer from the time serial of output variables of the system , the numerical simulation result shows that the parameter observer proposed in this paper can identify the unknown parameters of the system quickly and exactly no matter if the parameters keep invariable or change in some rule , and the identifying speed is faster than the method in [ 117 - 118 ] , when the unknown parameters are being identified , vith parameter compensator , it can synchronizes two hyperchaotic systems completely even if some parameters mismatch ( 2 )采用文献[ 117 - 118 ]提出的参数辨识方法，通过选取更一般的增益函数： l _ i ( x _ i ) = kx _ ii = 1 , 2 , 3并根据系统输出变量的时间序列给出参数观测器的初始值来进行参数辨识，数值模拟结果表明：采用本文的参数观测器，在系统参数固定或变化的情况下，都可对系统未知参数实现快速高精度辨识，辨识的速度快于文献[ 117 - 118 ]提出的方法；在辨识参数的同时，结合参数补偿器，使两个参数不匹配的超混沌系统同步。
A new biased estimator so - called ridge type - generalized inverse ( rg1 ) estimator is constructed after summing - up the historical and present condition of biased estimation theory in surveying data processing . the prosperities of rg1 estimator are studied especially by pitman ' s criteria . the other biased estimator so - called partial root root ( prr ) estimator is generated 通过对有偏估计理论在测量数据处理中的应用历史和现状进行总结和分析，构造了未知参数的一种新的有偏估计方法? ?岭型广义逆估计，对其性质特别是在pitman准则下的若干性质进行了讨论；接下来构造了另一种新的有偏估计方法? ?部分根方估计，该估计的最大特点在于它是一种部分压缩估计。
The analysis shows that by using correction function processing to the collected signals , the periodicity of the signal can be checked conveniently , the frequency - domain response of linear systems with uncertain parameters can be identified , useful signals can be checked out and extracted from the noise 由分析可知，对采集到的信号做相关函数的处理可以方便地对信号的周期性进行检测，确定未知参数的线性系统的频域响应，检测噪声中有用信号，并对噪声中的信号进行提取。
3 . in regarding to fetch in the non - parameter gauss background model parameter , used many images constitution matrix characteristic value to take the non - parameter gauss background model the unknown parameter . has solved this algorithm consumption memory in a big way , parameter renewal difficulty and so on , the experiment indicated this method was effective 3 .在求取非参数高斯背景模型中的参数时,将多张图像所构成的矩阵特征值作为非参数高斯背景模型的未知参数,解决该模型消耗内存大、参数更新困难等缺陷,实验结果表明该方法效果良好,能够满足带钢表面缺陷提取的任务。
