P
Peng Shi
Researcher at University of Adelaide
Publications - 1601
Citations - 80441
Peng Shi is an academic researcher from University of Adelaide. The author has contributed to research in topics: Control theory & Nonlinear system. The author has an hindex of 137, co-authored 1371 publications receiving 65195 citations. Previous affiliations of Peng Shi include Harbin Engineering University & Harbin University of Science and Technology.
Papers
More filters
Journal ArticleDOI
Set-Membership Estimation for Complex Networks Subject to Linear and Nonlinear Bounded Attacks
TL;DR: A novel set-membership estimation model against unknown but bounded attacks is presented and two sufficient conditions are derived to guarantee the existence of the set- membership estimators for the cases that the attack functions are linear and nonlinear, respectively.
Journal ArticleDOI
The effect of topical ramipril and losartan cream in inhibiting scar formation.
Bin Zheng,Qing-Qing Fang,Xiao-Feng Wang,Bang-Hui Shi,Wan-Yi Zhao,Chun-Ye Chen,Min-Xia Zhang,Li-Yun Zhang,Yan-Yan Hu,Peng Shi,Lie Ma,Wei-Qiang Tan +11 more
TL;DR: These findings indicate that local application of angiotensin converting enzyme inhibitor drugs (ACEIs) and angiotENSin receptor blocker drugs (ARBs) can reduce scarring by reducing the expression of collagen I, collagen III, phosphorylated small mothers against decapentaplegic 3 (p-Smad3) and transforming growth factor-β 1 (TGF-β1).
Journal ArticleDOI
Optimal guaranteed cost filtering for Markovian jump discrete-time systems
Magdi S. Mahmoud,Peng Shi +1 more
TL;DR: In this paper, a robust steady-state estimator for a class of uncertain discrete-time systems with Markovian jump parameters was proposed. But the robustness of the estimator depends on the assumption that the estimation error covariance is within a certain bound for all admissible uncertainties.
Journal ArticleDOI
New criteria for stochastic suppression and stabilization of hybrid functional differential systems
Song Zhu,Peng Shi,Cheng-Chew Lim +2 more
Journal ArticleDOI
New global asymptotic stability criterion for neural networks with discrete and distributed delays
TL;DR: By the Lyapunov-Krasovskii functional approach, a new delay-dependent stability criterion is derived in terms of linear matrix inequalities (LMIs) that allows the time delay to be a fast time-varying function.