Identification of Wiener models with binary-valued output observations

被引：0

作者：

Zhao, Yanlong ^{[1
]}

Wang, Le Yi ^{[2
]}

Yin, G. George ^{[3
]}

Zhang, Ji-Feng ^{[1
]}

机构：

[1] Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China

[2] Wayne State Univ, Dept Elect & Comp Engn, Detroit, MI 48202 USA

[3] Wayne State Univ, Dept Math, Detroit, MI 48202 USA

来源：

2006 CHINESE CONTROL CONFERENCE, VOLS 1-5 | 2006年

关键词：

identification; binary-valued observations; Wiener model; joint identifiability;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This work focuses on system identification for Wiener models, whose outputs are measured by binary sensors. It begins with the development of joint identifiability. Then, using periodic inputs, empirical distributions are used to construct identification algorithms. Convergence of the algorithms is established, and associated recursive algorithms are also developed.

引用

页码：1622 / +

页数：2

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