Privacy-preserving nonlinear observer design using contraction analysis
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IEEE
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http://xplorestaging.ieee.org/ielx7/7396016/7402066/07402922.pdf?arnumber=7402922
Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Edge Differential Privacy for Algebraic Connectivity of Graphs;2021 60th IEEE Conference on Decision and Control (CDC);2021-12-14
2. Some novel aspects of the positive linear observer problem: Differential privacy and optimal l1 sensitivity;Journal of the Franklin Institute;2020-12
3. Differentially Private Nonlinear Observers;Differential Privacy for Dynamic Data;2020
4. Differentially private nonlinear observer design using contraction analysis;International Journal of Robust and Nonlinear Control;2018-11-12
5. Differential Privacy and the l 1 Sensitivity of Positive Linear Observers * *This work was supported with the financial support of the Science Foundation Ireland grant 13/RC/2094 and co-funded under the European Regional Development Fund through the Southern & Eastern Regional Operational Programme to Lero - the Irish Software Research Centre (www.lero.ie);IFAC-PapersOnLine;2017-07
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