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Spacecraft formation reconfiguration trajectory planning with avoidance constraints using adaptive pigeon-inspired optimization.

, , , , and . Sci. China Inf. Sci., 62 (7): 70209:1-70209:3 (2019)

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Diagnosis of Intermittent Scan Chain Faults Through a Multistage Neural Network Reasoning Process., , , , , , and . IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 39 (10): 3044-3055 (2020)Improving scan chain diagnostic accuracy using multi-stage artificial neural networks., , , , , , and . ASP-DAC, page 341-346. ACM, (2019)On Byzantine Distributed Sequential Change Detection with Multiple Hypotheses., , and . ISIT, page 2209-2213. IEEE, (2019)A study on multiple wearable sensors for activity recognition., , , , and . DSC, page 449-452. IEEE, (2017)Asymptotic Optimality in Byzantine Distributed Quickest Change Detection., , and . CoRR, (2019)Asymptotic Optimality in Byzantine Distributed Quickest Change Detection., , and . IEEE Trans. Inf. Theory, 67 (9): 5942-5962 (2021)Adaptive Segmentation Method for Evaluating of Choroidal Thickness on Optical Coherence Tomography., , and . ICDSP, page 61-64. ACM, (2018)Interpreting Latent Representation in Neural Radiance Fields for Manipulating Object Semantics., , , and . ICIP, page 470-474. IEEE, (2023)Design and Analysis of Cost-Cognizant Test Case Prioritization Using Genetic Algorithm with Test History., , , and . COMPSAC, page 413-418. IEEE Computer Society, (2010)A Tight Converse to the Asymptotic Performance of Byzantine Distributed Sequential Change Detection., , and . ISIT, page 2404-2408. IEEE, (2019)