南京信息工程大学学报2016，Vol.8Issue(6)：481-498,18.DOI:10.13878/j.cnki.jnuist.2016.06.001
辅助模型辨识方法（6）：性能分析
Auxiliary model based identification methods.Part F:Performance Analysis
摘要
Abstract
Performance analysis of identification methods is the important and difficult projects in the area of system identification. Once one new identification method is born, its convergence analysis appears. The auxiliary model identification is a branch of system identification and has become a large family of identification methods, their convergence brings many projects.This paper studies the consistent convergence of the auxiliary model (AM) based stochastic gradient ( SG ) algorithm, the AM recursive least squares ( RLS ) algorithm, the AM multi⁃innovation SG algorithm,the interval⁃varying AM SG algorithm and the interval⁃varying AM RLS algorithm for out⁃put⁃error systems, and analyzes approximately the convergence of the AM recursive generalized extended least squares algorithm for Box⁃Jenkins systems.关键词
参数估计/递推辨识/最小二乘/辅助模型辨识思想/多新息辨识理论/递阶辨识原理/耦合辨识概念/滤波辨识理念/线性系统Key words
parameter estimation/recursive identification/least squares/auxiliary model identification idea/multi-innovation identification theory/hierarchical identification principle/coupling identification concept/filtering identifi-cation idea/linear system分类
信息技术与安全科学引用本文复制引用
丁锋..辅助模型辨识方法（6）：性能分析[J].南京信息工程大学学报,2016,8(6):481-498,18.基金项目
国家自然科学基金（61273194）；江苏省自然科学基金（ BK2012549）；高等学校学科创新引智“111计划” （）
