Supervised Analysis Dictionary Learning: Application In Consumer Electronics Appliance Classification

PROCEEDINGS OF THE FOURTH ACM IKDD CONFERENCES ON DATA SCIENCES (CODS '17)(2017)

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摘要
The objective of this paper is to estimate if an electrical appliance is 'ON' based on their common mode electromagnetic (CM EMI) emissions. The assumption being that, a user by knowing the state of the appliance can make an informed decision whether to keep it running or switch it off to save power. Here, state estimation of a single appliance is formulated as a classification problem. A new technique called analysis dictionary learning is proposed to generate features from CM EMI. The proposed method outperforms feature extraction based on deep learning techniques as well as a state-of-the-art information theoretic feature extraction technique based on Conditional Likelihood Maximization.
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关键词
Non-intrusive load monitoring,supervised learning,dictionary learning
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