Decision-Based System Identification and Adaptive Resource Allocation

被引：0

作者：

Guo, Jin ^{[1
]}

Mu, Biqiang ^{[2
]}

Wang, Le Yi ^{[2
]}

Yin, George ^{[3
]}

Xu, Lijian ^{[2
]}

机构：

[1] Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, 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：

2014 IEEE 53RD ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC) | 2014年

关键词：

System identification; decision; reliability; resource allocation; complexity; COMPLEXITY; UNCERTAINTY; INFORMATION;

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：

System identification extracts information from a system's operational data to derive a representative model for the system. Studies of system identification have been concentrated on estimation algorithms and their convergence. Focusing on optimal resource allocation under a given reliability requirement, this paper studies identification complexity and its relations to decision making. Dynamic resource assignments are investigated. Resource allocation algorithms are developed and their convergence properties are established. Illustrative examples demonstrate better resource management than worst-case strategies when our algorithms are applied.

引用

页码：340 / 345

页数：6

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