Publications by authors named "Xinmiao Sun"
Article Synopsis
- Recent trends in underwater target recognition involve deep learning models, typically using either 1D or 2D approaches for time-domain signals and time-frequency spectra.
- This paper introduces a new temporal 2D modeling method that combines 1D and 2D techniques for classifying ship radiation noise, leveraging periodic characteristics of time-domain signals to enhance long-term correlation insights.
- The study shows that this hybrid method improves model accuracy by 0.9% and reduces parameter count by 30%, while also comparing the effectiveness of models trained on time-domain signals versus time-frequency representations, noting that time-domain models are more sensitive and space-efficient.
This paper investigates the distributed robust group output synchronization problem of heterogeneous uncertain linear leader-follower multi-agent systems (MASs), whose followers have nonidentical and parameter uncertain dynamics. To achieve cooperative tracking with multiple targets, a new group synchronization framework based upon the output regulation technique is established. In the underlying directed communication topology, all nonidentical followers are divided into several subgroups.
View Article and Find Full Text PDFAnomaly Detection in Discrete Manufacturing Systems by Pattern Relation Table Approaches.
Sensors (Basel)
October 2020
Anomaly detection for discrete manufacturing systems is important in intelligent manufacturing. In this paper, we address the problem of anomaly detection for the discrete manufacturing systems with complicated processes, including parallel processes, loop processes, and/or parallel with nested loop sub-processes. Such systems can generate a series of discrete event data during normal operations.
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