南京信息工程大学学报
南京信息工程大學學報
남경신식공정대학학보
JOURNAL OF NANJING UNIVERSITY OF INFORMATION SCIENCE & TECHNOLOGY
2014年
4期
289-305
,共17页
参数估计%迭代搜索原理%梯度搜索%最小二乘%数据滤波技术%辅助模型辨识思想%递阶辨识原理%耦合辨识概念%多变量系统
參數估計%迭代搜索原理%梯度搜索%最小二乘%數據濾波技術%輔助模型辨識思想%遞階辨識原理%耦閤辨識概唸%多變量繫統
삼수고계%질대수색원리%제도수색%최소이승%수거려파기술%보조모형변식사상%체계변식원리%우합변식개념%다변량계통
parameter estimation%iterative search principle%gradient search%least squares%data filtering technique%auxiliary model identification idea%hierarchical identification principle%coupling identification concept%multivariable system
针对多变量方程误差滑动平均系统，利用最小二乘原理和迭代搜索原理，给出了增广随机梯度辨识方法、递推增广最小二乘辨识方法、梯度迭代辨识方法和最小二乘迭代辨识方法。针对多变量方程误差滑动平均系统和多变量方程误差自回归滑动平均系统，将多变量系统分解为一些子系统，利用耦合辨识概念，讨论了梯度迭代辨识方法、部分耦合（子系统）梯度迭代辨识方法、子系统最小二乘迭代方法和部分耦合子系统最小二乘迭代辨识方法。进一步结合数据滤波技术，研究了多变量方程误差自回归滑动平均系统的子系统梯度迭代辨识方法、部分耦合（子系统）梯度迭代辨识方法、部分耦合子系统最小二乘迭代辨识方法。文中给出了几个典型算法的计算步骤。
針對多變量方程誤差滑動平均繫統，利用最小二乘原理和迭代搜索原理，給齣瞭增廣隨機梯度辨識方法、遞推增廣最小二乘辨識方法、梯度迭代辨識方法和最小二乘迭代辨識方法。針對多變量方程誤差滑動平均繫統和多變量方程誤差自迴歸滑動平均繫統，將多變量繫統分解為一些子繫統，利用耦閤辨識概唸，討論瞭梯度迭代辨識方法、部分耦閤（子繫統）梯度迭代辨識方法、子繫統最小二乘迭代方法和部分耦閤子繫統最小二乘迭代辨識方法。進一步結閤數據濾波技術，研究瞭多變量方程誤差自迴歸滑動平均繫統的子繫統梯度迭代辨識方法、部分耦閤（子繫統）梯度迭代辨識方法、部分耦閤子繫統最小二乘迭代辨識方法。文中給齣瞭幾箇典型算法的計算步驟。
침대다변량방정오차활동평균계통，이용최소이승원리화질대수색원리，급출료증엄수궤제도변식방법、체추증엄최소이승변식방법、제도질대변식방법화최소이승질대변식방법。침대다변량방정오차활동평균계통화다변량방정오차자회귀활동평균계통，장다변량계통분해위일사자계통，이용우합변식개념，토론료제도질대변식방법、부분우합（자계통）제도질대변식방법、자계통최소이승질대방법화부분우합자계통최소이승질대변식방법。진일보결합수거려파기술，연구료다변량방정오차자회귀활동평균계통적자계통제도질대변식방법、부분우합（자계통）제도질대변식방법、부분우합자계통최소이승질대변식방법。문중급출료궤개전형산법적계산보취。
For multivariable equation error moving average systems,this paper gives an extended stochastic gradient identification algorithm,a recursive extended least squares identification algorithm,a gradient based iterative( GI) identification algorithm and a least squares based iterative ( LSI ) identification algorithm, using the least squares principle and the iterative search principle. For multivariable equation error moving average systems and multivariable equation error autoregressive moving average systems,this paper uses the coupling identification con-cept and decomposes a multivariable system into several subsystems,derives the corresponding GI identification al-gorithm, partially coupled ( subsystem ) GI identification algorithm, subsystem LSI identification algorithm and partially coupled subsystem LSI identification algorithm.Furthermore,using the filtering technique,this paper studies the subsystem GI identification algorithm, partially coupled ( subsystem ) GI identification algorithm, partially coupled subsystem LSI identification algorithm for multivariable equation error autoregressive moving average sys-tems.The computational steps for several typical identification algorithms are provided.
