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DTSTAMP:20240626T180034Z
LOCATION:3008\, 3rd Floor
DTSTART;TZID=America/Los_Angeles:20240625T134500
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UID:dac_DAC 2024_sess136_RESEARCH426@linklings.com
SUMMARY:Neural Barrier Certificates Synthesis of NN-Controlled Continuous 
 Systems via Counterexample-Guided Learning
DESCRIPTION:Research Manuscript\n\nHanrui Zhao, Niuniu Qi, and Mengxin Ren
  (East China Normal University); Xia Zeng (Southwest University); Zhenbing
  Zeng (Shanghai University); and Zhengfeng Yang (East China Normal Univers
 ity)\n\nThere is a pressing need to ensure the safety of closed-loop syste
 ms with NN controllers. To address this issue, we propose a novel approach
  for generating barrier certificates, which combines counterexample-guided
  learning with efficient SOS-based verification. Our proposed method offer
 s an efficient verification procedure that solves three linear matrix ineq
 uality (LMI) constraint feasibility testing problems, instead of relying o
 n an SMT solver to verify the barrier certificate conditions. We conduct c
 omparison experiments on a set of benchmarks, demonstrating the advantages
  of our method in terms of efficiency and scalability, which enable effect
 ive verification of high-dimensional systems.\n\nTopic: EDA\n\nKeyword: De
 sign Verification and Validation\n\nSession Chairs: Maheshwar Chandrasekar
  (Synopsys) and Enrico Fraccaroli (University of Verona)
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