理论(学习稳定性)
正多边形
控制理论(社会学)
数学
计算机科学
控制(管理)
几何学
人工智能
机器学习
作者
PooGyeon Park,Jeong Wan Ko,Changki Jeong
出处
期刊:Automatica
[Elsevier]
日期:2010-11-21
卷期号:47 (1): 235-238
被引量:2436
标识
DOI:10.1016/j.automatica.2010.10.014
摘要
Whereas the upper bound lemma for matrix cross-product, introduced by Park (1999) and modified by Moon, Park, Kwon, and Lee (2001), plays a key role in guiding various delay-dependent criteria for delayed systems, the Jensen inequality has become an alternative as a way of reducing the number of decision variables. It directly relaxes the integral term of quadratic quantities into the quadratic term of the integral quantities, resulting in a linear combination of positive functions weighted by the inverses of convex parameters. This paper suggests the lower bound lemma for such a combination, which achieves performance behavior identical to approaches based on the integral inequality lemma but with much less decision variables, comparable to those based on the Jensen inequality lemma.
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