.png){kind=icon}
返回
Input design for structured nonlinear system identification
.png){kind=icon}
PRE
AI
DOI：10.1016/j.automatica.2010.02.029.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper is concerned with the input design problem for a class of structured nonlinear models. This class contains models described by an interconnection of known linear dynamic systems and unknown static nonlinearities. Many widely used model structures are included in this class The model class considered naturally accommodates a priori knowledge in terms of signal interconnections. Under certain structural conditions, the identification problem for this model class reduces to standard least squares We treat the input design problem in this situation. An expression for the expected estimate variance is derived. A method for synthesizing an informative input sequence that minimizes an upper bound on this variance is developed. This reduces to a convex optimization problem Features of the solution include parameterization of the expected estimate variance by the input distribution, and a graph-based method for input generation. (C) 2010 Elsevier Ltd. All rights reserved.
Keyword:
Experiment design
Linear/nonlinear models
Identification methods
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
5.9
论文数:
1.2W
被引数:
5.2W
机构
引用论文
.png){kind=icon}
分享收藏Shigella Antibiotic Resistance in Central Turkey: Comparison of the Years 1987‐1994 and 1995‐2002
OAAI
OAAI分享收藏
查看更多内容