Minghui Zhu, PhD

    • 1358 Citations
    • 16 h-Index
    20062020
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    Fingerprint Dive into the research topics where Minghui Zhu is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

    Stochastic systems Engineering & Materials Science
    State estimation Engineering & Materials Science
    Unknown Inputs Mathematics
    Motion planning Engineering & Materials Science
    State Estimation Mathematics
    Reinforcement learning Engineering & Materials Science
    Attack Mathematics
    Discrete-time Systems Mathematics

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    Research Output 2006 2020

    Simultaneous input and state estimation for stochastic nonlinear systems with additive unknown inputs

    Kim, H., Guo, P., Zhu, M. & Liu, P., Jan 1 2020, In : Automatica. 111, 108588.

    Research output: Contribution to journalArticle

    State estimation
    Error analysis
    Nonlinear systems
    Stochastic systems
    Covariance matrix

    A control-theoretic perspective on cyber-physical privacy: Where data privacy meets dynamic systems

    Lu, Y. & Zhu, M., Jan 1 2019, In : Annual Reviews in Control. 47, p. 423-440 18 p.

    Research output: Contribution to journalReview article

    Data privacy
    Dynamical systems
    Cyber Physical System

    MTD techniques for memory protection against zero-day attacks

    chen, P., Hu, Z., Xu, J., Zhu, M., Erbacher, R., Jajodia, S. & Liu, P., Jan 1 2019, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag, p. 129-155 27 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11830 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingChapter

    Attack
    Data storage equipment
    Zero
    Methodology
    Review
    1 Citation (Scopus)

    On convergence rates of game theoretic reinforcement learning algorithms

    Hu, Z., Zhu, M., Chen, P. & Liu, P., Jun 2019, In : Automatica. 104, p. 90-101 12 p.

    Research output: Contribution to journalArticle

    Reinforcement learning
    Learning algorithms

    Reinforcement learning for adaptive cyber defense against zero-day attacks

    Hu, Z., Chen, P., Zhu, M. & Liu, P., Jan 1 2019, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag, p. 54-93 40 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11830 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingChapter

    Reinforcement learning
    Reinforcement Learning
    Attack
    Zero
    Control theory