Conference Papers - 2016 by CHIMAN KWAN
— This paper describes a novel approach to sensor and actuator integrity monitoring. Multiple sen... more — This paper describes a novel approach to sensor and actuator integrity monitoring. Multiple sensor and actuator faults can be detected and isolated. Most importantly, fault magnitudes can be correctly estimated. Our approach is robust to disturbance and does not require additional sensors.
— This paper summarizes our research results on local active noise reduction. Our aim is to creat... more — This paper summarizes our research results on local active noise reduction. Our aim is to create a small quiet zone for astronauts in noisy spacecraft environments. A novel approach is proposed. Extensive simulations and preliminary real-time experiments demonstrate the efficacy of the proposed system.
Anomaly detection has been known to be a challenging, ill-posed problem due to the uncertainty of... more Anomaly detection has been known to be a challenging, ill-posed problem due to the uncertainty of anomaly and the interference of noise. In this paper, we propose a novel low rank anomaly detection algorithm in hyperspectral images (HSI), where three components are involved. First, due to the highly mixed nature of pixels in HSI, instead of using the raw pixel directly for anomaly detection, the proposed algorithm applies spectral unmixing algorithms to obtain the abundance vectors and uses these vectors for anomaly detection. Second , for better classification, a dictionary is built based on the mean-shift clustering of the abundance vectors to better represent the highly-correlated background and the sparse anomaly. Finally, a low-rank matrix decomposition is proposed to encourage the sparse coefficients of the dictionary to be low-rank, and the residual matrix to be sparse. Anomalies can then be extracted by summing up the columns of the residual matrix. The proposed algorithm is evaluated on both synthetic and real datasets. Experimental results show that the proposed approach constantly achieves high detection rate while maintaining low false alarm rate regardless of the type of images tested.
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Conference Papers - 2016 by CHIMAN KWAN