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陈性敏

Personal Information

Associate Professor   Supervisor of Master's Candidates  

Research Field

My research interests are mainly in system identification and adaptive control, stochastic optimization and distributed optimization, and nonparametric statistics. The primary research focus is in to develop theory and algorithms for identification and adaptive control of stochastic systems, to provide efficient algorithms and theoretical guarantees for (distributed) optimization problems that arise in system control and machine learning. To solve these problems, the following mathematical tools are principally needed for both theoretical analysis and application implementations.

  • Stochastic approximation: to investigate the statistical properties, such as almost sure convergence, convergence rate, asymptotic normality and asymptotic efficiency.

  • Statistics and stochastic process: to offer stochastic analysis for proposed algorithms.

  • C0 semigroup theory: to prove the existence and uniqueness of solution, and to provide stability analysis, etc.