南京信息工程大学学报2016，Vol.8Issue(2)：97-115,19.DOI:10.13878/j.cnki.jnuist.2016.02.001
辅助模型辨识方法（2）：输入非线性输出误差系统
Auxiliary model identification methods. Part B:Input nonlinear output-error systems
摘要
Abstract
For input nonlinear output⁃error systems with known bases,this paper presents the over⁃parameterization model based auxiliary model ( AM) recursive identification methods,the over⁃parameterization model based AM hi⁃erarchical identification methods,the key term separation based AM recursive identification methods,the key term separation based AM two⁃stage recursive identification methods,the key term separation based AM three⁃stage re⁃cursive identification methods,the bilinear⁃in⁃parameter model decomposition based AM stochastic gradient identifi⁃cation methods and the bilinear⁃in⁃parameter model decomposition based AM recursive least squares identification methods.Finally,the computational efficiency and the computational steps of several typical identification algorithms are discussed.The convergence of the proposed algorithms needs further study.关键词
参数估计/递推辨识/梯度搜索/最小二乘/过参数化模型/关键项分离/模型分解/辅助模型辨识思想/递阶辨识原理/输入非线性系统Key words
parameter estimation/recursive identification/gradient search/least squares/over-parameterization model/key term separation/model decomposition/auxiliary model identification ideal/hierarchical identification principle/input nonlinear system分类
信息技术与安全科学引用本文复制引用
丁锋,陈慧波..辅助模型辨识方法（2）：输入非线性输出误差系统[J].南京信息工程大学学报,2016,8(2):97-115,19.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” （）
